mlelarge / graph_neural_netLinks
Expressive Power of Invariant and Equivariant Graph Neural Networks (ICLR 2021)
☆40Updated last year
Alternatives and similar repositories for graph_neural_net
Users that are interested in graph_neural_net are comparing it to the libraries listed below
Sorting:
- [ICML 2021] GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training (official implementation)☆106Updated 2 years ago
- ☆38Updated 5 years ago
- Code for Graph Normalizing Flows.☆62Updated 5 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 5 years ago
- ☆16Updated 5 years ago
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- ☆25Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆56Updated 3 years ago
- Official implementation for the paper: Permutation Invariant Graph Generation via Score-Based Generative Modeling☆111Updated 2 years ago
- Implicit Graph Neural Networks☆62Updated 3 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆56Updated 4 years ago
- informal exposition of Weisfeiler-Leman similarity☆28Updated 4 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- ☆28Updated 3 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆104Updated 5 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆79Updated 2 years ago
- ☆31Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- SignNet and BasisNet☆100Updated last year
- Neural Ensemble Search for Uncertainty Estimation and Dataset Shift☆33Updated last year
- ☆26Updated 6 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated last year
- Implementation of Directional Graph Networks in PyTorch and DGL☆118Updated 4 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆54Updated 2 years ago
- Official Pytorch Implementation of GraphiT☆109Updated 4 years ago
- Locally corrected Nyström (LCN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, …☆19Updated 2 years ago
- Source code for PairNorm (ICLR 2020)☆78Updated 5 years ago
- SetToGraph paper repository☆22Updated 4 years ago