9 citations · 16 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 9 cited
On Graph Neural Networks versus Graph-Augmented MLPs
Lei Chen, Zhengdao Chen, Joan Bruna
From the perspective of expressive power, this work compares multi-layer Graph Neural Networks (GNNs) with a simplified alternative that we call Graph-Augmented Multi-Layer Percept…
cs.LG2020
Can Graph Neural Networks Count Substructures?
Zhengdao Chen, Lei Chen, Soledad Villar +1
The ability to detect and count certain substructures in graphs is important for solving many tasks on graph-structured data, especially in the contexts of computational chemistry…
cs.CV2019★ 7 cited
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator
Shunwang Gong, Lei Chen, Michael Bronstein +1
Intrinsic graph convolution operators with differentiable kernel functions play a crucial role in analyzing 3D shape meshes. In this paper, we present a fast and efficient intrinsi…