Rémi Louf's guest appearances

Rémi Louf

Indésciences Podcasts

Learning Bayesian Statistics

David Spiegelhalter

Andrew Gelman

Michael Lee

Baba Brinkman

Michael Kennedy

Allen Downey

Sean Taylor

Michael Faber

Matthew Kay

Michael Betancourt

Eric Ma

Karin Knudson

Colin Carroll

Osvaldo Martin

Chris Fonnesbeck

OwlTail

Episode sponsored by Paperpile: paperpile.comGet 20% off until December 31st with promo code GOODBAYESIAN21Bonjour my dear Bayesians! Yes, it was bound to happen one day — and this day has finally come. Here is the first ever 100% French speaking ‘Learn Bayes Stats’ episode! Who is to blame, you ask? Well, who better than Rémi Louf?Rémi currently works as a senior data scientist at Ampersand, a big media marketing company in the US. He is the author and maintainer of several open source libraries, including MCX and BlackJAX. He holds a PhD in statistical Physics, a Masters in physics from the Ecole Normale Supérieure and a Masters in Philosophy from Oxford University.I think I know what you’re wondering: how the hell do you go from physics to philosophy to Bayesian stats?? Glad you asked, as it was my first question to Rémi! He’ll also tell us why he created MXC and BlackJax, what his main challenges are when working on open-source projects, and what the future of PPLs looks like to him.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, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, 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, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin and Philippe Labonde.Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)Links from the show:Rémi on GitHub: https://github.com/rloufRémi on Twitter: https://twitter.com/remiloufRémi's website: https://rlouf.github.io/BlackJAX -- Fast &amp; modular sampling library: https://github.com/blackjax-devs/blackjaxMCX -- Probabilistic programs on CPU &amp; GPU, powered by JAX: https://github.com/rlouf/mcxaeppl, Tools for a PPL in Aesara: https://github.com/aesara-devs/aepplFrench Presidents' popularity dashboard: https://www.pollsposition.com/popularityHow to model presidential approval (in French): https://anchor.fm/pollspolitics/episodes/10-Comment-Modliser-la-Popularit-e121jh2LBS #23, Bayesian Stats in Business &amp; Marketing, with Elea McDonnel Feit: https://www.learnbayesstats.com/episode/23-bayesian-stats-in-business-and-marketing-analytics-with-elea-mcdonnel-feitLBS #30, Symbolic Computation &amp; Dynamic Linear Models, with Brandon Willard: https://www.learnbayesstats.com/episode/symbolic-computation-dynamic-linear-models-brandon-willardThis podcast uses the following third-party services for analysis: Podcorn - https://podcorn.com/privacy

Episode sponsored by Paperpile: <a href="https://paperpile.com/" rel="noopener noreferrer nofollow" target="_blank">paperpile.com</a>Get 20% off until December 31st with promo code GOODBAYESIAN21Bonjour my dear Bayesians! Yes, it was bound to happen one day — and this day has finally come. Here is the first ever 100% French speaking ‘Learn Bayes Stats’ episode! Who is to blame, you ask? Well, who better than Rémi Louf?Rémi currently works as a senior data scientist at Ampersand, a big media marketing company in the US. He is the author and maintainer of several open source libraries, including MCX and BlackJAX. He holds a PhD in statistical Physics, a Masters in physics from the Ecole Normale Supérieure and a Masters in Philosophy from Oxford University.I think I know what you’re wondering: how the hell do you go from physics to philosophy to Bayesian stats?? Glad you asked, as it was my first question to Rémi! He’ll also tell us why he created MXC and BlackJax, what his main challenges are when working on open-source projects, and what the future of PPLs looks like to him.Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at <a href="https://bababrinkman.com/" rel="noopener noreferrer nofollow" target="_blank">https://bababrinkman.com/</a> !Thank you to my Patrons for making this episode possible!Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, 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, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin and Philippe Labonde.Visit <a href="https://www.patreon.com/learnbayesstats" rel="noopener noreferrer nofollow" target="_blank">https://www.patreon.com/learnbayesstats</a> to unlock exclusive Bayesian swag ;)Links from the show:<ul><li>Rémi on GitHub: <a href="https://github.com/rlouf" rel="noopener noreferrer nofollow" target="_blank">https://github.com/rlouf</a></li><li>Rémi on Twitter: <a href="https://twitter.com/remilouf" rel="noopener noreferrer nofollow" target="_blank">https://twitter.com/remilouf</a></li><li>Rémi's website: <a href="https://rlouf.github.io/" rel="noopener noreferrer nofollow" target="_blank">https://rlouf.github.io/</a></li><li>BlackJAX -- Fast &amp; modular sampling library: <a href="https://github.com/blackjax-devs/blackjax" rel="noopener noreferrer nofollow" target="_blank">https://github.com/blackjax-devs/blackjax</a></li><li>MCX -- Probabilistic programs on CPU &amp; GPU, powered by JAX: <a href="https://github.com/rlouf/mcx" rel="noopener noreferrer nofollow" target="_blank">https://github.com/rlouf/mcx</a></li><li>aeppl, Tools for a PPL in Aesara: <a href="https://github.com/aesara-devs/aeppl" rel="noopener noreferrer nofollow" target="_blank">https://github.com/aesara-devs/aeppl</a></li><li>French Presidents' popularity dashboard: <a href="https://www.pollsposition.com/popularity" rel="noopener noreferrer nofollow" target="_blank">https://www.pollsposition.com/popularity</a></li><li>How to model presidential approval (in French): <a href="https://anchor.fm/pollspolitics/episodes/10-Comment-Modliser-la-Popularit-e121jh2" rel="noopener noreferrer nofollow" target="_blank">https://anchor.fm/pollspolitics/episodes/10-Comment-Modliser-la-Popularit-e121jh2</a></li><li>LBS #23, Bayesian Stats in Business &amp; Marketing, with Elea McDonnel Feit: <a href="https://www.learnbayesstats.com/episode/23-bayesian-stats-in-business-and-marketing-analytics-with-elea-mcdonnel-feit" rel="noopener noreferrer nofollow" target="_blank">https://www.learnbayesstats.com/episode/23-bayesian-stats-in-business-and-marketing-analytics-with-elea-mcdonnel-feit</a></li><li>LBS #30, Symbolic Computation &amp; Dynamic Linear Models, with Brandon Willard: <a href="https://www.learnbayesstats.com/episode/symbolic-computation-dynamic-linear-models-brandon-willard" rel="noopener noreferrer nofollow" target="_blank">https://www.learnbayesstats.com/episode/symbolic-computation-dynamic-linear-models-brandon-willard</a></li></ul>This podcast uses the following third-party services for analysis: Podcorn - <a href="https://podcorn.com/privacy" rel="nofollow" target="_blank">https://podcorn.com/privacy</a>

#44 Building Bayesian Models at scale, with Rémi Louf

Pour ce nouveau podcast nous avons rencontré Rémi Louf, lauréat en 2016 du prix « Le Monde » de la recherche universitaire pour ses travaux de thèse mêlant des modèles de physique statistique à l'étude de l'urbanisme de nos villes. Nous vous souhaitons à tous une très bonne écoute !

HS Rémi Louf Approche physique stat pour théories urbaines