Episode
#150 Fast Bayesian Deep Learning, with David Rügamer, Emanuel Sommer & Jakob Robnik
- Podcast
- Learning Bayesian Statistics
- Published
- Jan 28, 2026
- Duration seconds
- 4827
- Processing state
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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 Scaling Bayesian Neural Networks 04:26 Origin Stories of the Researchers 09:46 Research Themes in Bayesian Neural Networks 12:05 Making Bayesian Neural Networks Fast 16:19 Microcanonical Langevin Sampler Explained 22:57 Bottlenecks in Scaling Bayesian Neural Networks 29:09 Practical Tools for Bayesian Neural Networks 36:48 Trade-offs in Computational Efficiency and Posterior Fidelity 40:13 Exploring High Dimensional Gaussians 43:03 Practical Applications of Bayesian Deep Ensembles 45:20 Comparing Bayesian Neural Networks with Standard Approaches 50:03 Identifying Real-World Applications for Bayesian Methods 57:44 Future of Bayesian Deep Learning at Scale 01:05:56 The Evolution of Bayesian Inference Packages 01:10:39 Vision for the Future of Bayesian Statistics Thank you to my Patrons for making this episode possible! Come meet Alex at the Field of Play Conference in Manchester, UK, March 27, 2026! Links from the show : David Rügamer: * Website * Google Scholar * GitHub Emanuel Sommer: * Website * GitHub * Google Scholar Jakob Robnik: * Google Scholar * GitHub * Microcanonical Langevin paper * LinkedIn