
Andreas Munk
Researcher and entrepreneur in probabilistic programming and amortized inference, PhD from UBC who worked with Frank Wood and co-founded Evara to bring Bayesian inference into Excel; creator/contributor to PyProb and work on inference compilation and probabilistic surrogate networks.
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Apr 8, 2026 • 1h 54min
#155 Probabilistic Programming for the Real World, with Andreas Munk
Andreas Munk, researcher and entrepreneur in probabilistic programming who co-founded Evara and helped build PyProb. He discusses bridging deep learning with probabilistic programming. He explains inference compilation and amortized inference. He describes probabilistic surrogate networks for costly simulators. He demos embedding Bayesian workflows into Excel for practical decision-making.


