Summary of Universal Inceptive Gnns by Eliminating the Smoothness-generalization Dilemma, By Ming Gu et al.
Universal Inceptive GNNs by Eliminating the Smoothness-generalization Dilemmaby Ming Gu, Zhuonan Zheng, Sheng Zhou, Meihan…
Universal Inceptive GNNs by Eliminating the Smoothness-generalization Dilemmaby Ming Gu, Zhuonan Zheng, Sheng Zhou, Meihan…
Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimizationby Peng Tao, Kazuyuki Aihara, Luonan ChenFirst submitted…
Hybrid variable spiking graph neural networks for energy-efficient scientific machine learningby Isha Jain, Shailesh Garg,…
Grothendieck Graph Neural Networks Framework: An Algebraic Platform for Crafting Topology-Aware GNNsby Amirreza Shiralinasab Langari,…
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending against Poisoning Attacksby Ao Liu,…
Edge-Splitting MLP: Node Classification on Homophilic and Heterophilic Graphs without Message Passingby Matthias Kohn, Marcel…
Robustness of Graph Classification: failure modes, causes, and noise-resistant loss in Graph Neural Networksby Farooq…
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approachby Hang Gao, Chenhao…
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspectiveby Yushun…
Deep Learning-Enhanced Preconditioning for Efficient Conjugate Gradient Solvers in Large-Scale PDE Systemsby Rui Li, Song…