[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
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Updated
Aug 16, 2024 - Python
[ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
[ICML 2023] Official implementation of "A randomized schur complement based graph augmentor"
[NeurIPS GLFrontiers 2023] DIGNN, Implicit Graph Neural Diffusion Models
Official implementation of CoPHo (KDD 2026).
Enhancing Spatiotemporal Supply Chain Forecasting Using Virtual Node-Augmented Graph Diffusion for Improved Fuel Efficiency
atlas — few-label learning on a manifold. One label per class recovers ~95% of MNIST when the metric is good enough (graph diffusion), and hurts when it isn't. Visual, reproducible study of edge purity, phase transitions, and label budgets.
Code for "Scaling Diffusion Models to Large Sparse Graphs"
MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation (NeurIPS 2026)
Latent Graph Diffusion 论文复现 | 图扩散生成 + 节点分类 | PyTorch + PyG
Information-Geometric Adaptive Sampling for Graph Diffusion
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