317 citations · 721 across the 36 of their papers we have counts for
5 papers · 1 filter
Conditional Permutation Invariant Flows
Berend Zwartsenberg, Adam Ścibior, Matthew Niedoba +7
We present a novel, conditional generative probabilistic model of set-valued data with a tractable log density. This model is a continuous normalizing flow governed by permutation…
Parallel Tempering With a Variational Reference
Nikola Surjanovic, Saifuddin Syed, Alexandre Bouchard-Côté +1
Sampling from complex target distributions is a challenging task fundamental to Bayesian inference. Parallel tempering (PT) addresses this problem by constructing a Markov chain on…
MixFlows: principled variational inference via mixed flows
Zuheng Xu, Naitong Chen, Trevor Campbell
This work presents mixed variational flows (MixFlows), a new variational family that consists of a mixture of repeated applications of a map to an initial reference distribution. F…
Fast Bayesian Coresets via Subsampling and Quasi-Newton Refinement
Cian Naik, Judith Rousseau, Trevor Campbell
Bayesian coresets approximate a posterior distribution by building a small weighted subset of the data points. Any inference procedure that is too computationally expensive to be r…
Bayesian inference via sparse Hamiltonian flows
Naitong Chen, Zuheng Xu, Trevor Campbell
A Bayesian coreset is a small, weighted subset of data that replaces the full dataset during Bayesian inference, with the goal of reducing computational cost. Although past work ha…