16 citations · 30 across the 7 of their papers we have counts for
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3 papers · 1 filter
cs.CV2020★ 5 cited
Refactoring Policy for Compositional Generalizability using Self-Supervised Object Proposals
Tongzhou Mu, Jiayuan Gu, Zhiwei Jia +2
We study how to learn a policy with compositional generalizability. We propose a two-stage framework, which refactorizes a high-reward teacher policy into a generalizable student p…
cs.LG2020★ 3 cited
Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks
Hao Tang, Zhiao Huang, Jiayuan Gu +2
Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Tak…
cs.LG2020★ 16 cited
Belief Propagation Neural Networks
Jonathan Kuck, Shuvam Chakraborty, Hao Tang +4
Learned neural solvers have successfully been used to solve combinatorial optimization and decision problems. More general counting variants of these problems, however, are still l…