{"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":"#151 Diffusion Models in Python, a Live Demo with Jonas Arruda","slug":"151-diffusion-models-in-python-a-live-demo-with-jonas-arruda","published_at":"2026-02-12T12:30:00+00:00","page_url":"https://stenobird.com/podcast/learning-bayesian-statistics/151-diffusion-models-in-python-a-live-demo-with-jonas-arruda","show_page_url":"https://stenobird.com/podcast/learning-bayesian-statistics","url":"https://api.riverside.com/hosting-analytics/media/db592db4c42e5fc76c47a5ab9e20f70c63b23dd3dcbf88d9f6e44da3291b791a/eyJlcGlzb2RlSWQiOiIxYzA2YzRjYy0wNjAwLTRlYTgtYTU3ZS0wMGI4NmE3MTQzMjgiLCJwb2RjYXN0SWQiOiI3OWUwYTRmYi05N2FiLTRlOTUtYTg3NS0yNGE4YjllZTI3ZGEiLCJhY2NvdW50SWQiOiI2NDQ4M2JiZWM3ZjQ1MTFhYThjMzE1Y2QiLCJwYXRoIjoibWVkaWEvY2xpcHMvNjk4ZDQ5ZWZjN2MyNTY0ZDI0NmU3MDAzL2FsZXhhbmRyZS1hbmRvcnJhcy1zdHVkaW8tY29tcG9zZXItMjAyNi0yLTEyX180LTMzLTMubXAzIn0=.mp3","audio_url":"https://api.riverside.com/hosting-analytics/media/db592db4c42e5fc76c47a5ab9e20f70c63b23dd3dcbf88d9f6e44da3291b791a/eyJlcGlzb2RlSWQiOiIxYzA2YzRjYy0wNjAwLTRlYTgtYTU3ZS0wMGI4NmE3MTQzMjgiLCJwb2RjYXN0SWQiOiI3OWUwYTRmYi05N2FiLTRlOTUtYTg3NS0yNGE4YjllZTI3ZGEiLCJhY2NvdW50SWQiOiI2NDQ4M2JiZWM3ZjQ1MTFhYThjMzE1Y2QiLCJwYXRoIjoibWVkaWEvY2xpcHMvNjk4ZDQ5ZWZjN2MyNTY0ZDI0NmU3MDAzL2FsZXhhbmRyZS1hbmRvcnJhcy1zdHVkaW8tY29tcG9zZXItMjAyNi0yLTEyX180LTMzLTMubXAzIn0=.mp3","summary":"• Support & get perks ! • Proudly sponsored by PyMC Labs ! • Intro to Bayes and Advanced Regression courses (first 2 lessons free) Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work ! Chapters: 00:00 Exploring Generative AI and Scientific Modeling 10:27 Understanding Simulation-Based Inference (SBI) and Its Applications 15:59 Diffusion Models in Simulation-Based Inference 19:22 Live Coding Session: Implementing Baseflow for SBI 34:39 Analyzing Results and Diagnostics in Simulation-Based Inference 46:18 Hierarchical Models and Amortized Bayesian Inference 48:14 Understanding Simulation-Based Inference (SBI) and Its Importance 49:14 Diving into Diffusion Models: Basics and Mechanisms 50:38 Forward and Backward Processes in Diffusion Models 53:03 Learning the Score: Training Diffusion Models 54:57 Inference with Diffusion Models: The Reverse Process 57:36 Exploring Variants: Flow Matching and Consistency Models 01:01:43 Benchmarking Different Models for Simulation-Based Inference 01:06:41 Hierarchical Models and Their Applications in Inference 01:14:25 Intervening in the Inference Process: Adding Constraints 01:25:35 Summary of Key Concepts and Future Directions Thank you to my Patrons for making this episode possible! Links from the show: - Come meet Alex at the Field of Play Conference in Manchester, UK, March 27, 2026! - Jonas's Diffusion for SBI Tutorial & Review (Paper & Code) - The BayesFlow Library - Jonas on LinkedIn - Jonas on GitHub - Further reading for more mathematical details: Holderrieth & Erives - 150 Fast Bayesian Deep Learning, with David Rügamer, Emanuel Sommer & Jakob Robnik - 107 Amortized Bayesian Inference with Deep Neural Networks, with Marvin Schmitt","meta_description":"• Support & get perks ! • Proudly sponsored by PyMC Labs ! • Intro to Bayes and Advanced Regression courses (first 2 lessons free) Our theme music is…","key_points":[],"chapters":[],"topics":[],"duration_seconds":5743,"processing_state":"failed","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/learning-bayesian-statistics/episodes/151-diffusion-models-in-python-a-live-demo-with-jonas-arruda/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/151-diffusion-models-in-python-a-live-demo-with-jonas-arruda.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}