TheGravLab / A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-CoarseningLinks
Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)
☆16Updated 5 years ago
Alternatives and similar repositories for A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-Coarsening
Users that are interested in A-Unifying-Framework-for-Spectrum-Preserving-Graph-Sparsification-and-Coarsening are comparing it to the libraries listed below
Sorting:
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 3 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆84Updated last year
- The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020☆35Updated 4 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆96Updated 3 years ago
- ☆28Updated 4 years ago
- Gradient gating (ICLR 2023)☆53Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- Source code for PairNorm (ICLR 2020)☆79Updated 5 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- Scattering GCN: overcoming oversmoothness in graph convolutional networks☆25Updated 3 years ago
- [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…☆137Updated 3 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 3 years ago
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆30Updated 3 years ago
- ☆58Updated 3 years ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆125Updated 3 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 4 years ago
- Implicit Graph Neural Networks☆63Updated 3 years ago
- ☆25Updated 4 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆165Updated 3 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- ☆35Updated 6 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 5 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 4 years ago
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated last month
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆53Updated 5 years ago