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06/22/2023
On Addressing the Limitations of Graph Neural Networks
This report gives a summary of two problems about graph convolutional ne...
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04/28/2023
MUDiff: Unified Diffusion for Complete Molecule Generation
We present a new model for generating molecular data by combining discre...
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04/25/2023
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability
Homophily principle, i.e. nodes with the same labels are more likely to ...
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12/21/2022
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks
The core operation of current Graph Neural Networks (GNNs) is the aggreg...
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10/30/2022
When Do We Need GNN for Node Classification?
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by addit...
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10/14/2022
Revisiting Heterophily For Graph Neural Networks
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using...
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09/12/2021
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using...
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06/03/2021
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning
We present an end-to-end, model-based deep reinforcement learning agent ...
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08/20/2020
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
The core operation of Graph Neural Networks (GNNs) is the aggregation en...
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08/20/2020
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
The performance limit of Graph Convolutional Networks (GCNs) and the fac...
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09/19/2019
Revisit Policy Optimization in Matrix Form
In tabular case, when the reward and environment dynamics are known, pol...
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06/05/2019
