Good Statistics PhD programs for probML/BNP/RL?

[bayeslord]

I am trying to make my PhD apps list. The topics I'm most interested in are theory and applications to ML of:

1. Bayesian inference/statistical computing- MCMC and sampling methods, variational inference, normalizing flows and probabilistic ML (VAEs, diffusion models, etc)

2. Bayesian non parametrics esp Gaussian processes, (heard Austin is exceptional for this)

3. Reinforcement learning, bandit algorithms, Bayesian optimization (also related to second)

Could y'all recommend good professors and programs in these areas (apart from the standard top statML ones CMU Cal Stanford maybe lol)?
 

My profile for context: https://forum.thegradcafe.com/topic/167223-optimal-stopping-problem-for-phd-apps-is-a-year-for-an-ms-worth-it/

[bayessays]

Duke, UT Austin, and UCSC  are the big Bayesian places.  Given your interests, I'd also look at UC-Irvine.  As you said, the top departments will all have a couple people researching some of these topics (although Bayesian non-parametrics is a little rarer than the other topics).

[bayeslord]

Thanks! Did you mean UCSC? I couldn't find many people in UCSB working on Bayesian stuff but UCSC seems really good!

[bayessays]

Sorry, yes, I meant UCSC!