{"podcast":{"title":"Learning Bayesian Statistics","slug":"learning-bayesian-statistics","podcast_index_feed_id":1331380,"rss_url":"https://feeds.captivate.fm/learnbayesstats/","website_url":"https://www.learnbayesstats.com","image_url":"https://hosting-media.riverside.com/media/imports/podcasts/79e0a4fb-97ab-4e95-a875-24a8b9ee27da/2331893-1568966097324-58deab5a83dc6.jpg","author":"Alexandre Andorra","episode_count":199,"summary":"Are you a researcher or data scientist / analyst / ninja? Do you want to learn Bayesian inference, stay up to date or simply want to understand what Bayesian inference is? Then this podcast is for you! You'll hear from researchers and practitioners of all fields about how they use Bayesian statistics, and how in turn YOU can apply these methods in your modeling workflow. When I started learning Bayesian methods, I really wished there were a podcast out there that could introduce me to the methods, the projects and the people who make all that possible. So I created \"Learning Bayesian Statistics\", where you'll get to hear how Bayesian statistics are used to detect black matter in outer space, forecast elections or understand how diseases spread and can ultimately be stopped. But this show is not only about successes -- it's also about failures, because that's how we learn best. So you'll often hear the guests talking about what *didn't* work in their projects, why, and how they overcame these challenges. Because, in the end, we're all lifelong learners! My name is Alex Andorra by the way. By day, I'm a Senior data scientist. By night, I don't (yet) fight crime, but I'm an open-sour…","last_synced_at":null,"page_url":"https://stenobird.com/podcast/learning-bayesian-statistics"},"episode":{"title":"#104 Automated Gaussian Processes & Sequential Monte Carlo, with Feras Saad","slug":"104-automated-gaussian-processes-sequential-monte-carlo-with-feras-saad","published_at":"2024-04-16T11:00:00+00:00","page_url":"https://stenobird.com/podcast/learning-bayesian-statistics/104-automated-gaussian-processes-sequential-monte-carlo-with-feras-saad","show_page_url":"https://stenobird.com/podcast/learning-bayesian-statistics","url":"https://learnbayesstats.com/all-episodes/104-automated-gaussian-processes-sequential-monte-carlo-feras-saad","audio_url":"https://api.riverside.com/hosting-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.mp3","summary":"Proudly sponsored by PyMC Labs , the Bayesian Consultancy. Book a call , or get in touch ! My Intuitive Bayes Online Courses 1:1 Mentorship with me GPs are extremely powerful…. but hard to handle. One of the bottlenecks is learning the appropriate kernel. What if you could learn the structure of GP kernels automatically? Sounds really cool, but also a bit futuristic, doesn’t it? Well, think again, because in this episode, Feras Saad will teach us how to do just that! Feras is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. He received his PhD in Computer Science from MIT, and, most importantly for our conversation, he’s the creator of AutoGP.jl, a Julia package for automatic Gaussian process modeling. Feras discusses the implementation of AutoGP, how it scales, what you can do with it, and how you can integrate its outputs in your models. Finally, Feras provides an overview of Sequential Monte Carlo and its usefulness in AutoGP, highlighting the ability of SMC to incorporate new data in a streaming fashion and explore multiple modes efficiently. 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, Marcin Elantkowski, Adam C. Smith,…","meta_description":"Proudly sponsored by PyMC Labs , the Bayesian Consultancy. Book a call , or get in touch ! My Intuitive Bayes Online Courses 1:1 Mentorship with me GPs ar…","key_points":[],"chapters":[],"topics":[],"duration_seconds":5448,"processing_state":"failed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/learning-bayesian-statistics/episodes/104-automated-gaussian-processes-sequential-monte-carlo-with-feras-saad/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/learning-bayesian-statistics/104-automated-gaussian-processes-sequential-monte-carlo-with-feras-saad.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}