Hands-On Amortized Bayesian Inference

Description

**🎙️ Speakers:🎙️ Speakers:** Thomas Wiecki, PhD, Luca Fiaschi, PhD, and**⏰ Time:** 15:00 UTC / 8:00 AM PT / 11:00 AM ET / 5:00 PM Berlin Traditional MCMC methods like NUTS are the gold standard for parameter estimation, but they hit a wall when dealing with intractable likelihoods, complex simulation models, or real-time production demands where sampling cannot afford to take minutes or hours. Enter Amortized Bayesian Inference (ABI): a paradigm shift where generative AI architectures (such as Normalizing Flows, Diffusion Models, and Flow Matching) are trained offline to learn complex posterior distributions. Once trained, inference becomes a fast forward pass. In this hands-on webinar, Stefan Radev (Creator of BayesFlow and Assistant Professor at RPI) joins PyMC Labs to demonstrate how to train neural inference networks and integrate them directly with PyMC workflows. **What you'll take away** * **The Fundamentals of ABI:** How generative AI turns simulation models into instantaneous probabilistic inference engines. * Circumvent Intractable Likelihoods: How to train Neural Likelihood Estimators in BayesFlow and plug them into PyMC’s JAX backend for MCMC sampling. * **Train Heavy, Deploy Fast:** How to shift computational burden offline to achieve sub-second Bayesian inference in production environments. * **Diagnostics & Trust:** How to use Simulation-Based Calibration (SBC) and coverage diagnostics to ensure your neural network isn't "hallucinating" posteriors. * **Live Code Demo:** A step-by-step walkthrough building, training, and evaluating a BayesFlow model alongside PyMC. **Who should join** * Data Scientists & ML Engineers who want to deploy Bayesian models into real-time production pipelines. * PyMC & Stan Users looking to model complex simulator-based data without explicit likelihood functions. * Researchers & Quantitative Analysts interested in cutting-edge applications of Generative AI for model-based inference. 📜 **Outline of Talk / Agenda:** * 5 min: Introduction to PyMC Labs and speakers * 40 min: Panel discussion * 15 min: Q&A \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- **💼 About the speakers:** **Dr. Thomas Wiecki** **(** Founder of PyMC Labs) Co-author of PyMC, the leading platform for statistical data science. To help businesses solve some of their trickiest data science problems, he assembled a world-class team of Bayesian modelers and founded PyMC Labs - the Bayesian AI consultancy. He did his PhD at Brown University studying cognitive neuroscience. **Connect with Thomas:** 👉[ Linkedin ](https://www.linkedin.com/in/twiecki/)🧩 [Github](https://github.com/twiecki) **Dr. Luca Fiaschi (PyMC Labs Partner, Gen AI Vertical)** Luca helps organizations unlock the value of data and AI. With 15+ years of experience, he’s led and scaled teams at Mistplay, HelloFresh, Alibaba, and Stitch Fix, driving breakthroughs in personalization, marketing optimization, and causal modeling. He holds a PhD in Computer Science from Heidelberg University. **Connect with Luca**👉 [LinkedIn](https://www.linkedin.com/in/lfiaschi/)🧩[ Github](https://github.com/lfiaschi) **Stefan T. Radev, PhD (Assistant Professor, Creator of BayesFlow)** Stefan is an Assistant Professor at Rensselaer Polytechnic Institute and the principal investigator at BayesOps. He is the creator of BayesFlow, an open-source framework for simulation-based inference, and he's passionate about translating complex probabilistic thinking into usable tools for scientists, developers, and anyone who wants to make better decisions with data. **Connect with Stefan** 👉 [LinkedIn](https://www.linkedin.com/in/stefan-radev-21b713187/) \-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\-\- **📖 Code of Conduct:** Please note that participants are expected to abide by [PyMC's Code of Conduct.](https://github.com/pymc-devs/pymc/blob/main/CODE_OF_CONDUCT.md) **Connecting with PyMC Labs:** 🌐 Website: [https://www.pymc-labs.com/](https://www.pymc-labs.com/) 👥 LinkedIn: [https://www.linkedin.com/company/pymc-labs/](https://www.linkedin.com/company/pymc-labs/) 🐦 Twitter: [https://twitter.com/pymc_labs](https://twitter.com/pymc_labs) 🎥 YouTube: [https://www.youtube.com/c/PyMCLabs](https://www.youtube.com/c/PyMCLabs) 🤝 Meetup: [https://www.meetup.com/pymc-labs-online-meetup/](https://www.meetup.com/pymc-labs-online-meetup/) 🎮 Discord: [https://discord.gg/MARSCNemw3](https://discord.gg/MARSCNemw3)