Bayesian Inference and Deep Learning: Theory and Practice of Generative Models

IntroductionPurpose of this bookThis book depicts the path from Bayesian inference to deep learning as a single long-form technical volume. There is one central theme: how can we handle uncertainty in ...

4 Essential Books on R, Bayesian Methods, and Reinforcement Learning

Introduction The moment I felt the most cold sweat in my machine learning career was during an internal review when I was ...
Nature

Bayesian Inference and Model Misspecification

Bayesian inference offers a principled mechanism for updating beliefs by combining prior distributions with observed data via Bayes’s theorem. Central to this approach is the specification of a ...
Eos

How Can We Make Better Decisions About What Lies Underground?

Geophysical data offer incomplete clues about the subsurface. Bayesian inversion turns them into plausible scenarios and ...