ansonb / FeTA_TMLRLinks
This repository reproduces the results in the paper "How expressive are transformers in spectral domain for graphs?"(published in TMLR)
☆12Updated 2 years ago
Alternatives and similar repositories for FeTA_TMLR
Users that are interested in FeTA_TMLR are comparing it to the libraries listed below
Sorting:
- Spectral Graph Attention Network with Fast Eigen-approximation☆12Updated 3 years ago
- PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))☆16Updated 11 months ago
- CAT-Walk is an inducive method that learns hyperedge representations via a novel higher-order random walk, SetWalk.☆14Updated last year
- Signal compression and reconstruction on complexes preserving topological features via Discrete Morse Theory☆12Updated 3 years ago
- Graph Transformers for Large Graphs☆21Updated last year
- Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.☆20Updated 3 months ago
- Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'☆18Updated last year
- ☆29Updated 2 years ago
- ☆13Updated 4 years ago
- The implementation of HyperND from the Nonlinear Feature Diffusion on Hypergraphs paper☆13Updated 3 years ago
- Code for “ACE-HGNN: Adaptive Curvature ExplorationHyperbolic Graph Neural Network”☆15Updated 3 years ago
- ☆13Updated 4 years ago
- Source code for "Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation" (IJCAI 2020)☆17Updated 11 months ago
- PyTorch Codes for Haar Graph Pooling☆11Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆8Updated 4 years ago
- ☆19Updated last year
- The implementation of our AAAI 2020 paper "GSSNN: Graph Smoothing Splines Neural Network".☆20Updated 4 years ago
- ☆10Updated 10 months ago
- ☆12Updated 4 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated last year
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 5 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Official repository for Cell Attention Networks☆14Updated last year
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆15Updated last year
- ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.☆15Updated 10 months ago
- Ultrahyperbolic Representation Learning☆13Updated 4 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 3 years ago
- A benchmark of meaningful graph datasets with tabular node features☆14Updated 4 months ago
- Codes for Paper: From Hypergraph Energy Functions to Hypergraph Neural Networks☆21Updated last year