3 papers
cs.LG2021
Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flows
Holden Lee, Chirag Pabbaraju, Anish Sevekari +1
Normalizing flows are a widely used class of latent-variable generative models with a tractable likelihood. Affine-coupling (Dinh et al, 2014-16) models are a particularly common t…
cs.LG2020
Efficient semidefinite-programming-based inference for binary and multi-class MRFs
Chirag Pabbaraju, Po-Wei Wang, J. Zico Kolter
Probabilistic inference in pairwise Markov Random Fields (MRFs), i.e. computing the partition function or computing a MAP estimate of the variables, is a foundational problem in pr…
cs.LG2019
Learning Functions over Sets via Permutation Adversarial Networks
Chirag Pabbaraju, Prateek Jain
In this paper, we consider the problem of learning functions over sets, i.e., functions that are invariant to permutations of input set items. Recent approaches of pooling individu…