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06/26/2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks
Brain graphs, which model the structural and functional relationships be...
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05/24/2023
Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective
We investigate the question of whether the knowledge learned by graph ne...
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11/30/2021
A Dataset-Dispersion Perspective on Reconstruction Versus Recognition in Single-View 3D Reconstruction Networks
Neural networks (NN) for single-view 3D reconstruction (SVR) have gained...
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11/05/2021
Augmentations in Graph Contrastive Learning: Current Methodological Flaws Towards Better Practices
Graph classification has applications in bioinformatics, social sciences...
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02/12/2021
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks
Most graph neural networks (GNN) perform poorly in graphs where neighbor...
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08/26/2020
Benchmarking Semi-supervised Federated Learning
Federated learning promises to use the computational power of edge devic...
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06/20/2020
Generalizing Graph Neural Networks Beyond Homophily
We investigate the representation power of graph neural networks in the ...
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06/15/2020
