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12/11/2021
Leaping Through Time with Gradient-based Adaptation for Recommendation
Modern recommender systems are required to adapt to the change in user p...
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11/05/2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
Theoretical analyses for graph learning methods often assume a complete ...
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11/22/2020
Stacked Graph Filter
We study Graph Convolutional Networks (GCN) from the graph signal proces...
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05/03/2020
Graph Homomorphism Convolution
In this paper, we study the graph classification problem from the graph ...
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10/09/2019
A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks
We present a simple proof for the universality of invariant and equivari...
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05/23/2019
Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Graph neural networks have become one of the most important techniques t...
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05/05/2019