47 citations · 219 across the 37 of their papers we have counts for
3 papers · 1 filter
A Variational Perspective on Generative Flow Networks
Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent +1
Generative flow networks (GFNs) are a class of models for sequential sampling of composite objects, which approximate a target distribution that is defined in terms of an energy fu…
E-Valuating Classifier Two-Sample Tests
Teodora Pandeva, Tim Bakker, Christian A. Naesseth +1
We introduce a powerful deep classifier two-sample test for high-dimensional data based on E-values, called E-value Classifier Two-Sample Test (E-C2ST). Our test combines ideas fro…
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
Liyi Zhang, David M. Blei, Christian A. Naesseth
Variational inference often minimizes the "reverse" Kullbeck-Leibler (KL) KL(q||p) from the approximate distribution q to the posterior p. Recent work studies the "forward" KL KL(p…