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Classroom Contents
Enhancing Markov Chain Monte Carlo Sampling Methods with Deep Learning
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- 1 Intro
- 2 Probabilities and Expectations
- 3 Monte-Carlo Sampling
- 4 Sampling and Learning
- 5 Outline
- 6 Importance Sampling and Transport
- 7 Assisting MCMC Sampling with Normalizing Flows
- 8 MCMC with NF for Sampling of Random Fields
- 9 MCMC with NF for Bayesian Inference
- 10 Non-Equilibrium Importance Sampling (NEIS)
- 11 NEIS for Gaussian Mixtures in 5D & 10D
- 12 NEIS for Neal's Funnel Distribution in 100
- 13 Concluding remarks
