Podcast appearances and mentions of trey causey

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Best podcasts about trey causey

Latest podcast episodes about trey causey

Canada Human Resources News
July 29, 2024 - Responsible Use of AI in Recruitment

Canada Human Resources News

Play Episode Listen Later Jul 29, 2024 31:12


In this episode, Elena Bobyreva talks to Trey Causey, Head of Responsible AI & Senior Director of Data Science at Indeed, about using AI in hiring.Stay with us to get the latest HR updates. Follow us on: X @cadHRnews; LinkedIn @ Canada HR News Podcast for HR news and clips from this interview. It is becoming clear that HR professionals are staring to take AI very seriously.  According to Zippia, 65% of recruiters currently use AI in the recruitment process. because it reduces workloads, improves search and hiring processes and streamlines candidate experience. But AI comes with risk and different jurisdictions rollout laws to protect job seekers from irresponsible Ai practices.In the interview, we discuss:- Specific ways that Indeed helps recruiters to source the candidates and job seekers find jobs using AI- Implications of candidate using AI tools to apply for jobs- Risks of using AI instruments in hiring- Ways to ensure the ethical use of AI in our processes- How employers and job seekers feel regarding the use of AI in recruitment- Importance of maintaining human involvement in hiring- What the future may look like for AI in recruitmentFor video clips from the interview 

Learning Bayesian Statistics
#91, Exploring European Football Analytics, with Max Göbel

Learning Bayesian Statistics

Play Episode Listen Later Sep 20, 2023 64:13 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meAs you may know, I'm kind of a nerd. And I also love football — I've been a PSG fan since I'm 5 years old, so I've lived it all with this club.. And yet, I've never done a European-centered football analytics episode because, well, the US are much more advanced when it comes to sports analytics.But today, I'm happy to say this day has come: a sports analytics episode where we can actually talk about European football. And that is thanks to Maximilan Göbel.Max is a post-doctoral researcher in Economics and Finance at Bocconi University in Milan. Before that, he did his PhD in Economics at the Lisbon School of Economics and Management. Max is a very passionate football fan and played himself for almost 25 years in his local football club. Unfortunately, he had to give it up when starting his PhD — don't worry, he still goes to the gym, or goes running and sometimes cycling.Max is also a great cook, inspired by all kinds of Italian food, and an avid podcast listener — from financial news, to health and fitness content, and even a mysterious and entertaining Bayesian podcast…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau and Luis Fonseca.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Max's website:

Between Two Cairns
Mortzengersturm, The Mad Manticore of the Prismatic Peak

Between Two Cairns

Play Episode Listen Later Sep 7, 2023 53:15


Yochai & Brad review Mortzengersturm, The Mad Manticore of the Prismatic Peak by Trey Causey, and answer a mailbag question.Mailbag Question: How do keep track of what happens during a session?Thanks to Bobby McElver for the show's music.For listener questions, email betweentwocairns@gmail.com!Check out our Patreon to support the show. Also stickers.Find more Between Two Cairns here.

Learning Bayesian Statistics
#90, Demystifying MCMC & Variational Inference, with Charles Margossian

Learning Bayesian Statistics

Play Episode Listen Later Sep 6, 2023 97:36 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meWhat's the difference between MCMC and Variational Inference (VI)? Why is MCMC called an approximate method? When should we use VI instead of MCMC?These are some of the captivating (and practical) questions we'll tackle in this episode. I had the chance to interview Charles Margossian, a research fellow in computational mathematics at the Flatiron Institute, and a core developer of the Stan software.Charles was born and raised in Paris, and then moved to the US to pursue a bachelor's degree in physics at Yale university. After graduating, he worked for two years in biotech, and went on to do a PhD in statistics at Columbia University with someone named… Andrew Gelman — you may have heard of him.Charles is also specialized in pharmacometrics and epidemiology, so we also talked about some practical applications of Bayesian methods and algorithms in these fascinating fields.Oh, and Charles' life doesn't only revolve around computers: he practices ballroom dancing and pickup soccer, and used to do improvised musical comedy!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar and Matt Rosinski.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Charles' website: https://charlesm93.github.io/Charles on Twitter: https://twitter.com/charlesm993Charles on GitHub:

Learning Bayesian Statistics
#89 Unlocking the Science of Exercise, Nutrition & Weight Management, with Eric Trexler

Learning Bayesian Statistics

Play Episode Listen Later Aug 23, 2023 119:50 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIf you've ever tried to lose fat or gain muscle, you may have noticed… it's not easy. But it's precisely its complexity that makes the science of exercise and nutrition fascinating.This is the longest LBS episode so far, and you'll understand why pretty quickly: we covered a very wide range of topics, starting with the concept of metabolic adaptation and how our physiology and brain react to caloric deficits or caloric surpluses.We also talked about the connection between metabolic adaptation and exercise energy compensation, shedding light on the interactions between the two, and how they make weight management more complex.Statistics are of utmost importance in these endeavors, so of course we touched on how Bayesian stats can help mitigate the challenges of low sample sizes and over-focus on average treatment effect.My guest for this marathon episode, is no other than Eric Trexler. Currently at the Department of Evolutionary Anthropology of Duke University, Eric conducts research on metabolism and cardiometabolic health. He has a PhD in Human Movement Science from UNC Chapel Hill, and has published dozens of peer-reviewed research papers related to exercise, nutrition, and metabolism.In addition, Eric is a former professional bodybuilder and has been coaching clients with goals related to health, fitness, and athletics since 2009.In other words, get comfy for a broad and nerdy conversation about the mysteries related to energy expenditure regulation, weight management, and evolutionary mechanisms underpinning current health challenges.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt

Learning Bayesian Statistics
#88 Bridging Computation & Inference in Artificial Intelligent Systems, with Philipp Hennig

Learning Bayesian Statistics

Play Episode Listen Later Aug 10, 2023 71:50


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meToday, we're gonna learn about probabilistic numerics — what they are, what they are good for, and how they relate computation and inference in artificial intelligent systems.To do this, I have the honor of hosting Philipp Hennig, a distinguished expert in this field, and the Chair for the Methods of Machine Learning at the University of Tübingen, Germany. Philipp studied in Heidelberg, also in Germany, and at Imperial College, London. Philipp received his PhD from the University of Cambridge, UK, under the supervision of David MacKay, before moving to Tübingen in 2011. Since his PhD, he has been interested in the connection between computation and inference. With international colleagues, he helped establish the idea of probabilistic numerics, which describes computation as Bayesian inference. His book, Probabilistic Numerics — Computation as Machine Learning, co-authored with Mike Osborne and Hans Kersting, was published by Cambridge University Press in 2022 and is also openly available online. So get comfy to explore the principles that underpin these algorithms, how they differ from traditional numerical methods, and how to incorporate uncertainty into the decision-making process of these algorithms.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar and Matt Rosinski.Visit

Learning Bayesian Statistics
#87 Unlocking the Power of Bayesian Causal Inference, with Ben Vincent

Learning Bayesian Statistics

Play Episode Listen Later Jul 30, 2023 68:38


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meI'll be honest — this episode is long overdue. Not only because Ben Vincent is a friend, fellow PyMC Labs developer, and outstanding Bayesian modeler. But because he works on so many fascinating topics — so I'm all the happier to finally have him on the show!In this episode, we're gonna focus on causal inference, how it naturally extends Bayesian modeling, and how you can use the CausalPy open-source package to supercharge your Bayesian causal inference. We'll also touch on marketing models and the pymc-marketing package, because, well, Ben does a lot of stuff ;)Ben got his PhD in neuroscience at Sussex University, in the UK. After a postdoc at the University of Bristol, working on robots and active vision, as well as 15 years as a lecturer at the Scottish University of Dundee, he switched to the private sector, working with us full time at PyMC Labs — and that is a treat!When he's not working, Ben loves running 5k's, cycling in the forest, lifting weights, and… learning about modern monetary theory.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Ben's website:

Learning Bayesian Statistics
#86 Exploring Research Synchronous Languages & Hybrid Systems, with Guillaume Baudart

Learning Bayesian Statistics

Play Episode Listen Later Jul 14, 2023 58:43


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Listen on PoduramaMy Intuitive Bayes Online Courses1:1 Mentorship with meThis episode is unlike anything I've covered so far on the show. Let me ask you: Do you know what a research synchronous language is? What about hybrid systems? Last try: have you heard of Zelus, or ProbZelus?If you answered “no” to one of the above, then you're just like me! And that's why I invited Guillaume Baudart for this episode — to teach us about all these fascinating topics!Guillaume is a researcher in programming languages who works on ProbZelus, a probabilistic extension to Zelus, itself a research synchronous language to implement hybrid systems. To simplify, Zelus is a modeling framework to simulate the dynamics of systems both smooth and subject to discrete dynamics — if you've ever worked with ODEs, you may be familiar with these terms.If you're not — great, Guillaume will explain everything in the episode! And I know it might sound niche, but this kind of approach actually has very important applications — such as proving that there are no bugs in a program.Guillaume did his PhD at École Normale Supérieure, in Paris, working on reactive programming languages and quasi-periodic systems. He then worked in the AI programming team of IBM Research, before coming back to the École Normale Supérieure, working mostly on reactive and probabilistic programming.In his free time, Guillaume loves spending time with his family, playing the violin with friends, and… cooking!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant...

Learning Bayesian Statistics
#85 A Brief History of Sports Analytics, with Jim Albert

Learning Bayesian Statistics

Play Episode Listen Later Jun 27, 2023 66:11 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meIn this episode, I am honored to talk with a legend of sports analytics in general, and baseball analytics in particular. I am of course talking about Jim Albert.Jim grew up in the Philadelphia area and studied statistics at Purdue University. He then spent his entire 41-year academic career at Bowling Green State University, which gave him a wide diversity of classes to teach – from intro statistics through doctoral level.As you'll hear, he's always had a passion for Bayesian education, Bayesian modeling and learning about statistics through sports. I find that passion fascinating about Jim, and I suspect that's one of the main reasons for his prolific career — really, the list of his writings and teachings is impressive; just go take a look at the show notes.Now an Emeritus Professor of Bowling Green, Jim is retired, but still an active tennis player and writer on sports analytics — his blog, “Exploring Baseball with R”, is nearing 400 posts!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Jim's website: https://bayesball.github.io/Jim's baseball blog: https://baseballwithr.wordpress.com/Jim on GitHub: https://github.com/bayesballJim on Twitter: https://twitter.com/albertbayesJim on...

Learning Bayesian Statistics
#84 Causality in Neuroscience & Psychology, with Konrad Kording

Learning Bayesian Statistics

Play Episode Listen Later Jun 13, 2023 65:42 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meThis is another installment in our neuroscience modeling series! This time, I talked with Konrad Kording, about the role of Bayesian stats in neuroscience and psychology, electrophysiological data to study what neurons do, and how this helps explain human behavior.Konrad studied at ETH Zurich, then went to UC London and MIT for his postdocs. After a decade at Northwestern University, he is now Penn Integrated Knowledge Professor at the University of Pennsylvania.As you'll hear, Konrad is particularly interested in the question of how the brain solves the credit assignment problem and similarly how we should assign credit in the real world (through causality). Building on this, he is also interested in applications of causality in biomedical research.And… he's also a big hiker, skier and salsa dancer!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony and Joshua Meehl.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Konrad's lab: https://kordinglab.com/Konrad's lab on GitHub: https://github.com/KordingLabKonrad's lab on Twitter: https://twitter.com/KordingLabLBS #81, Neuroscience of Perception: Exploring the Brain, with Alan Stocker:

Learning Bayesian Statistics
#83 Multilevel Regression, Post-Stratification & Electoral Dynamics, with Tarmo Jüristo

Learning Bayesian Statistics

Play Episode Listen Later May 25, 2023 77:21 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meOne of the greatest features of this podcast, and my work in general, is that I keep getting surprised. Along the way, I keep learning, and I meet fascinating people, like Tarmo Jüristo.Tarmo is hard to describe. These days, he's heading an NGO called Salk, in the Baltic state called Estonia. Among other things, they are studying and forecasting elections, which is how we met and ended up collaborating with PyMC Labs, our Bayesian consultancy.But Tarmo is much more than that. Born in 1971 in what was still the Soviet Union, he graduated in finance from Tartu University. He worked in finance and investment banking until the 2009 crisis, when he quit and started a doctorate in… cultural studies. He then went on to write for theater and TV, teaching literature, anthropology and philosophy. An avid world traveler, he also teaches kendo and Brazilian jiu-jitsu.As you'll hear in the episode, after lots of adventures, he established Salk, and they just used a Bayesian hierarchical model with post-stratification to forecast the results of the 2023 Estonian parliamentary elections and target the campaign efforts to specific demographics.Oh, and let thing: Tarmo is a fan of the show — I told you he was a great guy ;)Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh and Grant Pezzolesi.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Tarmo on GitHub: https://github.com/tarmojuristoTarmo on...

Learning Bayesian Statistics
#82 Sequential Monte Carlo & Bayesian Computation Algorithms, with Nicolas Chopin

Learning Bayesian Statistics

Play Episode Listen Later May 5, 2023 66:35


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with me------------------------------------------------------------------------------Max Kochurov's State of Bayes Lecture Series: https://www.youtube.com/playlist?list=PL1iMFW7frOOsh5KOcfvKWM12bjh8zs9BQSign up here for upcoming lessons: https://www.meetup.com/pymc-labs-online-meetup/events/293101751/------------------------------------------------------------------------------We talk a lot about different MCMC methods on this podcast, because they are the workhorses of the Bayesian models. But other methods exist to infer the posterior distributions of your models — like Sequential Monte Carlo (SMC) for instance. You've never heard of SMC? Well perfect, because Nicolas Chopin is gonna tell you all about it in this episode!A lecturer at the French university of ENSAE since 2006, Nicolas is one of the world experts on SMC. Before that, he graduated from Ecole Polytechnique and… ENSAE, where he did his PhD from 1999 to 2003.Outside of work, Nicolas enjoys spending time with his family, practicing aikido, and reading a lot of books.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady and Kurt TeKolste.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Old episodes...

Learning Bayesian Statistics
#81 Neuroscience of Perception: Exploring the Brain, with Alan Stocker

Learning Bayesian Statistics

Play Episode Listen Later Apr 24, 2023 74:55


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Did you know that the way your brain perceives speed depends on your priors? And it's not the same at night? And it's not the same for everybody?This is another of these episodes I love where we dive into neuroscience, how the brain works, and how it relates to Bayesian stats. It's actually a follow-up to episode 77, where Pascal Wallisch told us how the famous black and blue dress tells a lot about our priors about how we perceive the world. So I strongly recommend listening to episode 77 first, and then come back here, to have your mind blown away again, this time by Alan Stocker.Alan was born and raised in Switzerland. After a PhD in physics at ETH Zurich, he somehow found himself doing neuroscience, during a postdoc at NYU. And then he never stopped — still leading the Computational Perception and Cognition Laboratory of the University of Pennsylvania.But Alan is also a man of music (playing the piano when he can), a man of coffee (he'll never refuse an olympia cremina or a kafatek) and a man of the outdoors (he loves trashing through deep powder with his snowboard).Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady and Kurt TeKolste.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Alan's website: https://www.sas.upenn.edu/~astocker/lab/members-files/alan.phpNoise characteristics and prior expectations in human visual speed perception: https://www.nature.com/articles/nn1669Combining efficient coding with Bayesian inference as a...

Learning Bayesian Statistics
#80 Bayesian Additive Regression Trees (BARTs), with Sameer Deshpande

Learning Bayesian Statistics

Play Episode Listen Later Apr 11, 2023 69:05 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I'm sure you know at least one Bart. Maybe you've even used one — but you're not proud of it, because you didn't know what you were doing. Thankfully, in this episode, we'll go to the roots of regression trees — oh yeah, that's what BART stands for. What were you thinking about?Our tree expert will be no one else than Sameer Deshpande. Sameer is an assistant professor of Statistics at the University of Wisconsin-Madison. Prior to that, he completed a postdoc at MIT and earned his Ph.D. in Statistics from UPenn.On the methodological front, he is interested in Bayesian hierarchical modeling, regression trees, model selection, and causal inference. Much of his applied work is motivated by an interest in understanding the long-term health consequences of playing American-style tackle football. He also enjoys modeling sports data and was a finalist in the 2019 NFL Big Data Bowl.Outside of Statistics, he enjoys cooking, making cocktails, and photography — sometimes doing all of those at the same time…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, and Arkady.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Sameer's website: https://skdeshpande91.github.io/Sameer on GitHub: https://github.com/skdeshpande91Sameer on Twitter: https://twitter.com/skdeshpande91 Sameer on Google Scholar: https://scholar.google.com/citations?user=coVrnWIAAAAJ&hl=enLBS #50 Ta(l)king Risks & Embracing...

Learning Bayesian Statistics
#79 Decision-Making & Cost Effectiveness Analysis for Health Economics, with Gianluca Baio

Learning Bayesian Statistics

Play Episode Listen Later Mar 17, 2023 67:48


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Decision-making and cost effectiveness analyses rarely get as important as in the health systems — where matters of life and death are not a metaphor. Bayesian statistical modeling is extremely helpful in this field, with its ability to quantify uncertainty, include domain knowledge, and incorporate causal reasoning.Specialized in all these topics, Gianluca Baio was the person to talk to for this episode. He'll tell us about this kind of models, and how to understand them.Gianluca is currently the head of the department of Statistical Science at University College London. He studied Statistics and Economics at the University of Florence (Italy), and completed a PhD in Applied Statistics, again at the beautiful University of Florence.He's also a very skilled pizzaiolo — so now I have two reasons to come back to visit Tuscany…Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, and Arkady.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Gianluca's website: https://gianluca.statistica.it/Gianluca on GitHub: https://github.com/giabaio Gianluca on Mastodon: https://mas.to/@gianlubaioGianluca on Twitter: https://twitter.com/gianlubaioGianluca on...

Learning Bayesian Statistics
#78 Exploring MCMC Sampler Algorithms, with Matt D. Hoffman

Learning Bayesian Statistics

Play Episode Listen Later Mar 1, 2023 62:41 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!Matt Hoffman has already worked on many topics in his life – music information retrieval, speech enhancement, user behavior modeling, social network analysis, astronomy, you name it.Obviously, picking questions for him was hard, so we ended up talking more or less freely — which is one of my favorite types of episodes, to be honest.You'll hear about the circumstances Matt would advise picking up Bayesian stats, generalized HMC, blocked samplers, why do the samplers he works on have food-based names, etc.In case you don't know him, Matt is a research scientist at Google. Before that, he did a postdoc in the Columbia Stats department, working with Andrew Gelman, and a Ph.D at Princeton, working with David Blei and Perry Cook.Matt is probably best known for his work in approximate Bayesian inference algorithms, such as stochastic variational inference and the no-U-turn sampler, but he's also worked on a wide range of applications, and contributed to software such as Stan and TensorFlow Probability.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode and Gabriel Stechschulte.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Matt's website: http://matthewdhoffman.com/Matt on Google Scholar: https://scholar.google.com/citations?hl=en&user=IeHKeGYAAAAJ&view_op=list_worksThe No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo: https://www.jmlr.org/papers/volume15/hoffman14a/hoffman14a.pdfTuning-Free Generalized Hamiltonian Monte Carlo:

Learning Bayesian Statistics
#77 How a Simple Dress Helped Uncover Hidden Prejudices, with Pascal Wallisch

Learning Bayesian Statistics

Play Episode Listen Later Feb 13, 2023 69:01 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I love dresses. Not on me, of course — I'm not nearly elegant enough to pull it off. Nevertheless, to me, dresses are one of the most elegant pieces of clothing ever invented.And I like them even more when they change colors. Well, they don't really change colors — it's the way we perceive the colors that can change. You remember that dress that looked black and blue to some people, and white and gold to others? Well that's exactly what we'll dive into and explain in this episode.Why do we literally see the world differently? Why does that even happen beyond our consciousness, most of the time? And cherry on the cake: how on Earth could this be related to… priors?? Yes, as in Bayesian priors!Pascal Wallisch will shed light on all these topics in this episode. Pascal is a professor of Psychology and Data Science at New York University, where he studies a diverse range of topics including perception, cognitive diversity, the roots of disagreement and psychopathy.Originally from Germany, Pascal did his undergraduate studies at the Free University of Berlin. He then received his PhD from the University of Chicago, where he studied visual perception.In addition to scientific articles on psychology and neuroscience, he wrote multiple books on scientific computing and data science. As you'll hear, Pascal is a wonderful science communicator, so it's only normal that he also writes for a general audience at Slate or the Creativity Post, and has given public talks at TedX and Think and Drink.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R and Nicolas Rode.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Pascal's website: https://blog.pascallisch.net/about/Pascal on Twitter:

Learning Bayesian Statistics
#76 The Past, Present & Future of Stan, with Bob Carpenter

Learning Bayesian Statistics

Play Episode Listen Later Feb 1, 2023 71:10 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!How does it feel to switch careers and start a postdoc at age 47? How was it to be one of the people who created the probabilistic programming language Stan? What should the Bayesian community focus on in the coming years?These are just a few of the questions I had for my illustrious guest in this episode — Bob Carpenter. Bob is, of course, a Stan developer, and comes from a math background, with an emphasis on logic and computer science theory. He then did his PhD in cognitive and computer sciences, at the University of Edinburgh.He moved from a professor position at Carnegie Mellon to industry research at Bell Labs, to working with Andrew Gelman and Matt Hoffman at Columbia University. Since 2020, he's been working at Flatiron Institute, a non-profit focused on algorithms and software for science.In his free time, Bob loves to cook, see live music, and play role playing games — think Monster of the Week, Blades in Dark, and Fate.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin and Raphaël R.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Bob's website: https://bob-carpenter.github.ioBob on GitHub: https://github.com/bob-carpenterBob on Google Scholar: https://scholar.google.com.au/citations?user=kPtKWAwAAAAJ&hl=enStat modeling blog: https://statmodeling.stat.columbia.eduStan home page:

Learning Bayesian Statistics
#75 The Physics of Top Gun 2 Maverick, with Jason Berndt

Learning Bayesian Statistics

Play Episode Listen Later Jan 20, 2023 67:26 Transcription Available


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!If you're a nerd like me, you're always curious about the physics of any situation. So, obviously, when I watched Top Gun 2, I became fascinated by the aerodynamics of fighters jets. And it so happens that one of my friends used to be a fighter pilot for the Canadian army… Immediately, I thought this would make for a cool episode — and here we are!Actually, Jason Berndt wanted to be a pilot from the age of 3. When he was 6, he went to an air show, and then specifically wanted to become a fighter pilot. In his teens, he learned how to fly saliplanes, small single engine aircrafts. At age 22, he got a bachelor's in aero engineering from the royal military college, and then — well, he'll tell you the rest in the episode.Now in his thirties, he owns real estate and created his own company, My Two Brows, selling temporary eyebrow tattoos — which, weirdly enough, is actually related to his time in the army…In his free time, Jason plays the guitar, travels around the world (that's actually how we met), and loves chasing adrenaline however he can (paragliding, scuba diving, you name it!).Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin and Raphaël R.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:My Two Brows website: https://mytwobrows.com/My Two Brows on Instagram: https://www.instagram.com/my_two_brows/My Two Brows on YouTube: https://www.youtube.com/channel/UC6eQgQ4qoGE2RStDJkumUGgPyMC Labs Workshop – Hierarchical Bayesian Modeling of Survey Data with Post-stratification:

The Retro Hour (Retro Gaming Podcast)
360: Curse of Monkey Island and The Dig with Bill Tiller - The Retro Hour EP359

The Retro Hour (Retro Gaming Podcast)

Play Episode Listen Later Jan 6, 2023 103:42


We chat to LucasArts graphics legend Bill Tiller who worked on titles such as the hugely ambitious The Dig, the brilliant Curse of Monkey Island and Star Wars: Rebel Assault. A Vampyre Story - Super Deluxe: https://bit.ly/3GIryFP Please visit our amazing sponsors and help to support the show: Bitmap Books https://www.bitmapbooks.com/ Check out PCBWay at https://pcbway.com for all your PCB needs Get 3 months of ExpressVPN for FREE: https://expressvpn.com/retro Thanks to our latest Patreon backers, in the Hall of Fame this week: Trey Causey, Lukas Valadez, Kieran Masterton, Graham Scott We need your help to ensure the future of the podcast, if you'd like to help us with running costs, equipment and hosting, please consider supporting us on Patreon: https://theretrohour.com/support/ https://www.patreon.com/retrohour Get your Retro Hour merchandise: https://bit.ly/33OWBKd Join our Discord channel: https://discord.gg/GQw8qp8 Website: http://theretrohour.com Facebook: https://www.facebook.com/theretrohour/ Twitter: https://twitter.com/retrohouruk Instagram: https://www.instagram.com/retrohouruk/ Twitch: https://www.twitch.tv/theretrohour Upcoming events: Amiga Ireland: https://bit.ly/3ife62P Show notes: Lost Michael Jackson Sega game found: https://bit.ly/3VIKb0A   Cancelled Duke Nukem 4 eva leaks: https://bit.ly/3X8MJpT Duke Nukem first slice: https://bit.ly/3It6xjQ Atari ends VCS production: https://bit.ly/3vFqKv9 Lost Sega VR game made playable on modern VR: https://bit.ly/3CtUVZM

Learning Bayesian Statistics
#74 Optimizing NUTS and Developing the ZeroSumNormal Distribution, with Adrian Seyboldt

Learning Bayesian Statistics

Play Episode Listen Later Jan 5, 2023 72:16


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!We need to talk. I had trouble writing this introduction. Not because I didn't know what to say (that's hardly ever an issue for me), but because a conversation with Adrian Seyboldt always takes deliciously unexpected turns.Adrian is one of the most brilliant, interesting and open-minded person I know. It turns out he's courageous too: although he's not a fan of public speaking, he accepted my invitation on this show — and I'm really glad he did!Adrian studied math and bioinformatics in Germany and now lives in the US, where he enjoys doing maths, baking bread and hiking.We talked about the why and how of his new project, Nutpie, a more efficient implementation of the NUTS sampler in Rust. We also dived deep into the new ZeroSumNormal distribution he created and that's available from PyMC 4.2 onwards — what is it? Why would you use it? And when?Adrian will also tell us about his favorite type of models, as well as what he currently sees as the biggest hurdles in the Bayesian workflow.Each time I talk with Adrian, I learn a lot and am filled with enthusiasm — and now I hope you will too!Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey and Andreas Kröpelin.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:LBS on Twitter: https://twitter.com/LearnBayesStatsLBS on Linkedin: https://www.linkedin.com/company/learn-bayes-stats/

Learning Bayesian Statistics
#73 A Guide to Plotting Inferences & Uncertainties of Bayesian Models, with Jessica Hullman

Learning Bayesian Statistics

Play Episode Listen Later Dec 23, 2022 60:55


Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!I'm guessing you already tried to communicate the results of a statistical model to non-stats people — it's hard, right? I'll be honest: sometimes, I even prefer to take notes during meetings than doing that… But shhh, that's out secret.But all of this was before. Before I talked with Jessica Hullman. Jessica is the Ginny Rometty associate professor of computer science at Northwestern University.Her work revolves around how to design interfaces to help people draw inductive inferences from data. Her research has explored how to best align data-driven interfaces and representations of uncertainty with human reasoning capabilities, which is what we'll mainly talk about in this episode.Jessica also tries to understand the role of interactive analysis across different stages of a statistical workflow, and how to evaluate data visualization interfaces.Her work has been awarded with multiple best paper and honorable mention awards, and she frequently speaks and blogs on topics related to visualization and reasoning about uncertainty — as usual, you'll find the links in the show notes.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, James Ahloy, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bert≈rand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, David Haas, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox and Trey Causey.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)General links from the show:Jessica's website: http://users.eecs.northwestern.edu/~jhullman/ Jessica on Twitter: https://twitter.com/JessicaHullmanMidwest Uncertainty Collective:

Blogs on Tape
Episode 42 – Dead Wizard’s Estate Sale, by Trey Causey

Blogs on Tape

Play Episode Listen Later Nov 11, 2018 5:42


Episode 42 – Dead Wizard’s Estate Sale, by Trey Causey Reading performed by Nick LS Whelan. The original post can be found on the author’s blog. The music used is a selection from “Journey of Solitude,” composed and performed by Russel Cox, distributed through OverClocked Remix.

Becoming A Data Scientist Podcast
Becoming a Data Scientist Podcast Episode 10 – Trey Causey

Becoming A Data Scientist Podcast

Play Episode Listen Later May 1, 2016 55:56


Trey Causey is a data scientist with a background in psychology and sociology who, like Renee, is from Virginia. He has worked as a data scientist at a range of companies from zulily to ChefSteps, and has also developed some interesting sports analytics projects, including the New York Times 4th Down bot. Trey also has advice for people wanting to start a career in data science. Show Notes

Drink Spin Run: The RPG Talkshow Podcast

Let's all talk about why the mainstream sucks togetherOur Guests+Mike Evans+Ripley StonebrookShow Notes after the jumpGuest NotesMike EvansBlogs at https://wrathofzombie.wordpress.com/Creator of the Hubris Campaign Setting for the DCC RPGAt the time this was recorded, Hubris was on Kickstarter. The Kickstarter was very successful and in a few months, we should have more info to share on it!Ripley StonebrookCreator of the Lair of Sword & Sorcery zine, game & blog found here: http://lairofswordandsorcery.blogspot.com/Show NotesDonn was eating a pawpawYoon-Suin by David McGrogan (art by Matthew Adams)Adam has some serious opinions of NumeneraAnother shout out to David McGrogan and his blog Monsters & ManualsScrap Princess and Monster Manual Sewn From PantsWe talk about Zak Smith a bitTrey Causey & Strange StarsWarband InquisimundaWhiteHackDelving DeeperZzarchov Kowalski's Scenic Dunsmouth and Thulian EchoesThird RailWhat's the worst thing to come out of mainstream gaming in the last decade?Thanks for joining us for this episode of Drink Spin Run. If you like what you've heard, share us with your friends, leave us an iTunes review or send us an email at dsr@kickassistan.net. You can also support us at http://www.patreon.com/DSRCast. Our theme music was generously provided by the band Blue Snaggletooth (http://bluesnaggletooth.bandcamp.com). Once again, thanks for listening, you gorgeous listeners.

Drink Spin Run: The RPG Talkshow Podcast
Drink Spin Run S2 E2.1: Mike and Ripley

Drink Spin Run: The RPG Talkshow Podcast

Play Episode Listen Later Dec 10, 2015


"Sternum" isn't a dirty word... yet.Our Guests+Mike Evans+Ripley StonebrookShow Notes after the jumpGuest NotesMike EvansBlogs at https://wrathofzombie.wordpress.com/Creator of the Hubris Campaign Setting for the DCC RPGAt the time this was recorded, Hubris was on Kickstarter. The Kickstarter was very successful and in a few months, we should have more info to share on it!Ripley StonebrookCreator of the Lair of Sword & Sorcery zine, game & blog found here: http://lairofswordandsorcery.blogspot.com/Show NotesDrinkDr. Thirty's Blonde, Wychwood Brewing, Oxfordshire, UKMike was unapologetically drinking PBRMaple Bourbon Barrel Black Beer, Dark Horse, Marhsall, MIBell's Best Brown, Bell's Brewery, Kalamazoo, MISpinGhost BC, MelioraBrian Eno, Here Come the Warm JetsBeastie Boys, Check Your HeadNazarethUriah HeapJethro TullThe Dead Weather, Dodge And BurnKMFDM Carrie Nation & the SpeakeasySoggy Bog of Doom is on Mixcloud!Kings Go Forth, "One Day"Warsaw Village Band, "Nord" -- Not at all like Wardruna, but heyThe Sorcerers, s/tReadHellboy In Hell, Mike MignolaCopperhead, Jay FaerberFear Agent, Rick RemenderWhite Star, James SpahnStrange Stars, Trey CauseyWyatt Earp Speaks, Wyatt Earp & John Richard StevensHouse of Leaves, Mark Z. DanielewskiFilth, Irvine WelshA Red & Pleasant Land, Zak S.Death Frost Doom, Zak S & James RaggiWhiteHack, Christian MehrstramPerilous Wilds, Jason LutesSaga/Hellblazer/Fire Upon the Deep (see last episode)Run+Jason Hobbs ran 5e for Donn(Donn never ended up running DCC for that Saturday night group)Ripley is running LoSS on Roll20.net!Mike enjoyed running Beyond the Wall by Flatland Games (Adam ran this as our first Actual Play session of the season!)Adam was about to start running Metamorphosis Alpha 1e, running +Jobe Bittman's module "Death Ziggurat In Zero G"Thanks for joining us for this episode of Drink Spin Run. If you like what you've heard, share us with your friends, leave us an iTunes review or send us an email at dsr@kickassistan.net. You can also support us at http://www.patreon.com/DSRCast. Our theme music was generously provided by the band Blue Snaggletooth (http://bluesnaggletooth.bandcamp.com). Once again, thanks for listening, you gorgeous listeners.

Partially Derivative
S1E34: The Data of Sports

Partially Derivative

Play Episode Listen Later Sep 3, 2015 42:31


We’re joined by sports analytics luminaries Sean Lahman, author of the Lahman Baseball Database, Trey Causey, creator of The Spread, a blog about the data science of sports, and Greg Matthews, author of openWAR, a technique for predicting the worth of baseball players. We dig into how huge amounts of data...

Drink Spin Run: The RPG Talkshow Podcast

WSG Stacy Dellorfano & Mike EvansOur Guests+Stacy Dellorfano+Mike EvansGuest NotesStacy DellorfanoContessaRandomocity zineFrivology blogMike EvansWrath of Zombie blogHubris campaign settingShow NotesDrinkMike's Hard LemonadeCrunkle Sam, Clown Shoes Brewery, Ipswitch, MAQueen City Common, Red Clay Ciderworks, Charlotte, NCCulinan's Revival Irish Red, Roc Brewery, Rochester, NYSingle Chair, Magic Hat, Burlington, VTSpinPJ HarveyNick Cave, Murder BalladsLocrianSleater-KinneyBikini KillReel Big FishNirvanaPearl JamKing CrimsonCaptain BeefheartLouis ArmstrongBarrows, Imprecari IslandIn the Company of Serpents, Merging In LightReadSwords Against Wizardry, Fritz LeiberRed & Pleasant Land, Zak SmithLamentations of the Flame Princess Weird Fantasy RPGSwords & Wizardry RPGStrange Stars, Trey CauseyNova Express, William S. BurroughsRunAdam & Donn are playing in Stormbringer 1e with +Mark Donkers & +Shawn GatesDonn is running D&D 5e for his family & friendsStacy is running her developing RPG, Precious DarkMike is running the final playtest for his Hubris campaign setting Thanks for joining us for this episode of Drink Spin Run. We'd love to read your comments on the show, suggestions, where exactly we can stick what and other thinly-veiled threats. Send us your thoughts at dsr@kickassistan.net. Once again, thanks for listening, you gorgeous listeners.