tech-srl / bottleneck
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"
☆93Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for bottleneck
- ☆62Updated 4 years ago
- ☆149Updated 3 years ago
- Implicit Graph Neural Networks☆59Updated 3 years ago
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆97Updated 3 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆267Updated last year
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆85Updated last year
- Implementation of Directional Graph Networks in PyTorch and DGL☆115Updated 3 years ago
- Code for "Weisfeiler and Leman go sparse: Towards higher-order graph embeddings"☆22Updated 2 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆153Updated 11 months ago
- SIGN: Scalable Inception Graph Network☆94Updated 4 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆78Updated 2 months ago
- Source code for PairNorm (ICLR 2020)☆76Updated 4 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆119Updated 3 months ago
- Official Pytorch Implementation of GraphiT☆106Updated 3 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆24Updated 2 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆159Updated 2 years ago
- Gradient gating (ICLR 2023)☆52Updated last year
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆45Updated 3 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆111Updated 3 years ago
- NeurIPS 2021: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectu…☆133Updated 2 years ago
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)☆40Updated 2 years ago
- ☆92Updated last year
- ☆26Updated 3 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆23Updated 4 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆64Updated 7 months ago
- Official implementation of our FLAG paper (CVPR2022)☆141Updated 2 years ago
- Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)☆101Updated 2 years ago
- ☆41Updated 2 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆192Updated 8 months ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆125Updated 2 years ago