SwiftieH / IGNNLinks
Implicit Graph Neural Networks
☆63Updated 3 years ago
Alternatives and similar repositories for IGNN
Users that are interested in IGNN are comparing it to the libraries listed below
Sorting:
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆96Updated 3 years ago
- ☆31Updated 2 years ago
- SIGN: Scalable Inception Graph Network☆95Updated 4 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- ☆28Updated 4 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- Source code for PairNorm (ICLR 2020)☆79Updated 5 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆42Updated 4 years ago
- ☆62Updated 4 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
- Code for "Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification"☆53Updated 5 years ago
- Official Code of Decoupled Graph Convolution (DGC)☆16Updated 3 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- Code for reproducing results in GraphMix paper☆72Updated 2 years ago
- The official implementation of ''Can Graph Neural Networks Count Substructures?'' NeurIPS 2020☆35Updated 4 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆126Updated last year
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 5 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆264Updated 3 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆84Updated last year
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 4 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 3 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 3 years ago
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Code of "Breaking the Limits of Message Passing Graph Neural Networks" paper published in ICML2021☆41Updated 4 years ago