diningphil / continual_learning_for_graphsLinks
☆13Updated 4 years ago
Alternatives and similar repositories for continual_learning_for_graphs
Users that are interested in continual_learning_for_graphs are comparing it to the libraries listed below
Sorting:
- Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.☆20Updated 2 months ago
- Official Repository of "Graph Mixture Density Networks" (ICML 2021)☆26Updated 2 years ago
- ☆29Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- Official code for the paper `Neural Algorithmic Reasoning for Combinatorial Optimisation`☆17Updated last year
- Official code repository for the papers "Anti-Symmetric DGN: a stable architecture for Deep Graph Networks" accepted at ICLR 2023; "Non-D…☆13Updated 5 months ago
- This repository reproduces the results in the paper "How expressive are transformers in spectral domain for graphs?"(published in TMLR)☆12Updated 2 years ago
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆15Updated last year
- [ICML 2024] Recurrent Distance Filtering for Graph Representation Learning☆15Updated 11 months ago
- Code for reproducing experiments in "On the Ability of Graph Neural Networks to Model Interactions Between Vertices"☆25Updated last year
- PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))☆16Updated 11 months ago
- A pytorch-based implementation of Dirichlet Process Mixture Model (DPMM)☆10Updated 6 months ago
- Graph Transformers for Large Graphs☆21Updated last year
- Graph transport network (GTN), as proposed in "Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, an…☆15Updated 2 years ago
- This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph…☆28Updated this week
- MetA-Train to Explain☆18Updated 3 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 3 years ago
- ☆25Updated 3 years ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated last year
- Graph Positional and Structural Encoder☆50Updated 4 months ago
- Variational Graph Convolutional Networks☆23Updated 4 years ago
- Official implementation of the ICML2021 paper "Elastic Graph Neural Networks"☆41Updated 3 years ago
- Official Code Repository for the paper "Graph Ordering Attention Networks"☆21Updated last year
- [ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?☆12Updated 11 months ago
- ☆12Updated 4 years ago
- Code for “ACE-HGNN: Adaptive Curvature ExplorationHyperbolic Graph Neural Network”☆15Updated 3 years ago
- The implementation of HyperND from the Nonlinear Feature Diffusion on Hypergraphs paper☆13Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 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