68 citations · 162 across the 11 of their papers we have counts for
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cs.LG2019★ 68 cited
Symplectic Recurrent Neural Networks
Zhengdao Chen, Jianyu Zhang, Martin Arjovsky +1
We propose Symplectic Recurrent Neural Networks (SRNNs) as learning algorithms that capture the dynamics of physical systems from observed trajectories. An SRNN models the Hamilton…
cs.LG2019★ 37 cited
On the equivalence between graph isomorphism testing and function approximation with GNNs
Zhengdao Chen, Soledad Villar, Lei Chen +1
Graph Neural Networks (GNNs) have achieved much success on graph-structured data. In light of this, there have been increasing interests in studying their expressive power. One lin…