mengliu1998 / awesome-expressive-gnnLinks
A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)
☆124Updated last year
Alternatives and similar repositories for awesome-expressive-gnn
Users that are interested in awesome-expressive-gnn are comparing it to the libraries listed below
Sorting:
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆159Updated last year
- ☆155Updated 4 years ago
- Code for our paper "Attending to Graph Transformers"☆90Updated last year
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆54Updated 2 years ago
- ☆41Updated 3 years ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- All graph/GNN papers accepted at NeurIPS 2024.☆83Updated 10 months ago
- List of papers on NeurIPS2023☆89Updated last year
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 4 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆197Updated last year
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆96Updated 3 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆264Updated 3 years ago
- here you can find the material used for our Tutorials☆103Updated 3 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆71Updated last year
- ☆96Updated 2 years ago
- ☆89Updated last year
- List of papers on ICML2023.☆55Updated 2 years ago
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆97Updated last year
- Graph Positional and Structural Encoder☆53Updated 8 months ago
- Message Passing Neural Networks for Simplicial and Cell Complexes☆164Updated 2 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆82Updated 2 years ago
- Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric☆354Updated 3 months ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆202Updated 7 months ago
- Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxi…☆102Updated 4 years ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆98Updated 10 months ago
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆36Updated last year
- A list for GNNs and related works.☆99Updated 3 months ago
- All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.☆223Updated 10 months ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago