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05/17/2023
Edge Directionality Improves Learning on Heterophilic Graphs
Graph Neural Networks (GNNs) have become the de-facto standard tool for ...
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03/06/2023
Graph Positional Encoding via Random Feature Propagation
Two main families of node feature augmentation schemes have been explore...
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09/30/2022
Graph Neural Networks for Link Prediction with Subgraph Sketching
Many Graph Neural Networks (GNNs) perform poorly compared to simple heur...
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06/22/2022
Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries
Subgraph GNNs are a recent class of expressive Graph Neural Networks (GN...
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10/06/2021
Equivariant Subgraph Aggregation Networks
Message-passing neural networks (MPNNs) are the leading architecture for...
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06/23/2021
Weisfeiler and Lehman Go Cellular: CW Networks
Graph Neural Networks (GNNs) are limited in their expressive power, stru...
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03/04/2021
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
The pairwise interaction paradigm of graph machine learning has predomin...
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06/18/2020
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Graph Neural Networks (GNNs) have recently become increasingly popular d...
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06/16/2020
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
While Graph Neural Networks (GNNs) have achieved remarkable results in a...
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04/23/2020
SIGN: Scalable Inception Graph Neural Networks
Geometric deep learning, a novel class of machine learning algorithms ex...
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09/14/2019
Learning interpretable disease self-representations for drug repositioning
Drug repositioning is an attractive cost-efficient strategy for the deve...
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02/10/2019
