Towards Reinforcement Learning-based Flow Space Optimization

Towards Reinforcement Learning-based Flow Space OptimizationA Deep Paradigm Shift in Modern Bayesian Inference — From the Limits of MCMC/Variational Inference to Neural Processes and GFlowNetsIntroduc ...

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 ...