96 citations · 205 across the 9 of their papers we have counts for
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cs.LG2019★ 10 cited
Can Graph Neural Networks Help Logic Reasoning?
Yuyu Zhang, Xinshi Chen, Yuan Yang +4
Effectively combining logic reasoning and probabilistic inference has been a long-standing goal of machine learning: the former has the ability to generalize with small training da…
cs.LG2019★ 3 cited
GLAD: Learning Sparse Graph Recovery
Harsh Shrivastava, Xinshi Chen, Binghong Chen +4
Recovering sparse conditional independence graphs from data is a fundamental problem in machine learning with wide applications. A popular formulation of the problem is an …
cs.LG2019
Particle Flow Bayes' Rule
Xinshi Chen, Hanjun Dai, Le Song
We present a particle flow realization of Bayes' rule, where an ODE-based neural operator is used to transport particles from a prior to its posterior after a new observation. We p…