gasteigerjo / lcnLinks
Locally corrected Nyström (LCN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More" (ICML 2021)
☆19Updated 2 years ago
Alternatives and similar repositories for lcn
Users that are interested in lcn are comparing it to the libraries listed below
Sorting:
- Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, an…☆15Updated 2 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- Python code associated with the paper "A Unifying Framework for Spectrum-Preserving Graph Sparsification and Coarsening'' (NeurIPS, 2019)☆16Updated 4 years ago
- ☆29Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 5 years ago
- Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs☆34Updated 5 years ago
- ☆25Updated 3 years ago
- ☆28Updated 3 years ago
- Code for Online Graph Dictionary Learning☆17Updated 3 years ago
- ☆19Updated 10 months ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆41Updated 3 years ago
- [ICLR 2023] Link Prediction with Non-Contrastive Learning☆26Updated 2 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 4 years ago
- ☆24Updated 3 years ago
- Edge Proposal Sets for Link Prediction (https://arxiv.org/abs/2106.15810)☆23Updated last year
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.☆26Updated 3 years ago
- Equivalence Between Structural Representations and Positional Node Embeddings☆22Updated 5 years ago
- This is the official repository for the paper "Laplacian Features for Learning with Hyperbolic Space"☆13Updated 2 years ago
- Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport☆36Updated 4 years ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- ☆31Updated 2 years ago
- ☆14Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago