16 citations · 30 across the 7 of their papers we have counts for
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cs.LG2021
Equivariant Neural Network for Factor Graphs
Fan-Yun Sun, Jonathan Kuck, Hao Tang +1
Several indices used in a factor graph data structure can be permuted without changing the underlying probability distribution. An algorithm that performs inference on a factor gra…
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…