jctops / understanding-oversquashingLinks
☆42Updated 3 years ago
Alternatives and similar repositories for understanding-oversquashing
Users that are interested in understanding-oversquashing are comparing it to the libraries listed below
Sorting:
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆160Updated 2 years ago
- Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023☆36Updated 2 years ago
- Gradient gating (ICLR 2023)☆55Updated 2 years ago
- ☆31Updated last year
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆92Updated 2 years ago
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆28Updated 3 years ago
- GraphCON (ICML 2022)☆59Updated 3 years ago
- A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)☆124Updated 2 years ago
- List of papers on NeurIPS2023☆90Updated 2 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- A library for subgraph GNN based on pyg☆40Updated last year
- All graph/GNN papers accepted at NeurIPS 2024.☆84Updated last year
- Official repository for the paper "On Evaluation Metrics for Graph Generative Models"☆25Updated 3 years ago
- ☆25Updated last year
- ☆156Updated 4 years ago
- ☆23Updated last year
- ☆21Updated 2 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆71Updated last year
- Understanding and Extending Subgraph GNNs by Rethinking their Symmetries (NeurIPS 2022 Oral)☆41Updated 2 years ago
- A Note On Over-Smoothing for Graph Neural Network☆20Updated 5 years ago
- Official repository for On Over-Squashing in Message Passing Neural Networks (ICML 2023)☆16Updated 2 years ago
- Implementation of Directional Graph Networks in PyTorch and DGL☆117Updated 4 years ago
- The codebase and datasets for the IJCAI 2021 paper "The Surprising Power of Graph Neural Networks with Random Node Initialization".☆22Updated 4 years ago
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆129Updated 3 months ago
- SignNet and BasisNet☆102Updated 2 years ago
- Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"☆97Updated 3 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆265Updated 3 years ago
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆84Updated 2 years ago
- Graph Positional and Structural Encoder☆53Updated 10 months ago