3 papers
stat.CO2024
Running Markov Chain Monte Carlo on Modern Hardware and Software
Pavel Sountsov, Colin Carroll, Matthew D. Hoffman
Today, cheap numerical hardware offers huge amounts of parallel computing power, much of which is used for the task of fitting neural networks to data. Adoption of this hardware to…
cs.CV2024
Robust Inverse Graphics via Probabilistic Inference
Tuan Anh Le, Pavel Sountsov, Matthew D. Hoffman +3
How do we infer a 3D scene from a single image in the presence of corruptions like rain, snow or fog? Straightforward domain randomization relies on knowing the family of corruptio…
stat.ME2024
Nested : Assessing the convergence of Markov chain Monte Carlo when running many short chains
Charles C. Margossian, Matthew D. Hoffman, Pavel Sountsov +3
Recent developments in parallel Markov chain Monte Carlo (MCMC) algorithms allow us to run thousands of chains almost as quickly as a single chain, using hardware accelerators such…