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08/07/2023
Implicit Graph Neural Diffusion Based on Constrained Dirichlet Energy Minimization
Implicit graph neural networks (GNNs) have emerged as a potential approa...
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06/19/2023
Fairness-aware Message Passing for Graph Neural Networks
Graph Neural Networks (GNNs) have shown great power in various domains. ...
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05/23/2023
SyNDock: N Rigid Protein Docking via Learnable Group Synchronization
The regulation of various cellular processes heavily relies on the prote...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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02/15/2022
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift
Deep graph learning (DGL) has achieved remarkable progress in both busin...
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02/02/2022
Understanding Knowledge Integration in Language Models with Graph Convolutions
Pretrained language models (LMs) do not capture factual knowledge very w...
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11/14/2021
p-Laplacian Based Graph Neural Networks
Graph neural networks (GNNs) have demonstrated superior performance for ...
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05/30/2021
Robust Dynamic Network Embedding via Ensembles
Dynamic Network Embedding (DNE) has recently attracted considerable atte...
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06/08/2020
Understanding Graph Neural Networks from Graph Signal Denoising Perspectives
Graph neural networks (GNNs) have attracted much attention because of th...
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02/15/2019
Learning Topological Representation for Networks via Hierarchical Sampling
The topological information is essential for studying the relationship b...
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01/29/2019
