nkeriven / random-graph-gnnLinks
☆12Updated 4 years ago
Alternatives and similar repositories for random-graph-gnn
Users that are interested in random-graph-gnn are comparing it to the libraries listed below
Sorting:
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Updated 5 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆12Updated 5 years ago
- ☆31Updated 2 years ago
- Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning☆20Updated 3 years ago
- ☆28Updated 4 years ago
- Code for Graph Neural Networks Exponentially Lose Expressive Power for Node Classification.☆30Updated 5 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- PyTorch Codes for Haar Graph Pooling☆11Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated 2 years ago
- Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)☆16Updated 5 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- Graph matching and clustering by comparing heat kernels via optimal transport.☆27Updated 2 years ago
- ☆35Updated 6 years ago
- Graph Homomorphism Convolution (ICML'20)☆11Updated 2 years ago
- Geo2DR: A Python and PyTorch library for learning distributed representations of graphs.☆46Updated 2 years ago
- Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper☆50Updated 4 years ago
- ☆18Updated 3 years ago
- ☆11Updated 3 years ago
- Started as a Team Project for CS690D at UMass Amherst, now turning into pytorch implementation of hyperbolic neural networks using Poinca…☆12Updated 2 years ago
- code for the paper in NeurIPS 2019☆40Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.☆14Updated last year
- Code for Graph Normalizing Flows.☆63Updated 5 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, an…☆15Updated 2 years ago
- Pytorch Implementation of Graph Convolutional Kernel Networks☆54Updated 2 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- ☆25Updated 4 years ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated 2 years ago