lsj2408 / GraphNorm
[ICML 2021] GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training (official implementation)
☆104Updated 2 years ago
Alternatives and similar repositories for GraphNorm:
Users that are interested in GraphNorm are comparing it to the libraries listed below
- ☆39Updated 4 years ago
- Source code for PairNorm (ICLR 2020)☆76Updated 4 years ago
- Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]☆155Updated 2 years ago
- Implicit Graph Neural Networks☆60Updated 3 years ago
- ☆62Updated 4 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 3 years ago
- Expressive Power of Invariant and Equivariant Graph Neural Networks (ICLR 2021)☆39Updated last year
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆94Updated 2 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 4 years ago
- Official Pytorch Implementation of GraphiT☆107Updated 3 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆250Updated 3 years ago
- Official implementation of our FLAG paper (CVPR2022)☆142Updated 2 years ago
- ☆155Updated 3 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆86Updated last year
- ☆16Updated 4 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆194Updated 11 months ago
- [ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆110Updated 3 years ago
- [TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*,…☆126Updated 3 years ago
- Memory-Based Graph Networks☆101Updated 2 years ago
- Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling☆110Updated last year
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆103Updated 5 years ago
- [NeurIPS 2021]: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architec…☆132Updated 2 years ago
- Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch☆164Updated 2 years ago
- AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations☆100Updated 4 years ago
- Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)☆269Updated last year
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆120Updated 6 months ago
- The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields☆57Updated 4 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆25Updated 2 years ago