subgraph23 / homomorphism-expressivityLinks
[ICLR 2024 Oral] Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness.
☆16Updated last year
Alternatives and similar repositories for homomorphism-expressivity
Users that are interested in homomorphism-expressivity are comparing it to the libraries listed below
Sorting:
- Reference implementation for SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators (ICML …☆26Updated 2 years ago
- [ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.☆23Updated last year
- ☆20Updated last year
- ☆21Updated last year
- Rex Ying's Ph.D. Thesis, Stanford University☆42Updated 2 years ago
- [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)☆104Updated last year
- [Preprint] Graph State Space Convolution (GSSC)☆13Updated 11 months ago
- Official Implementation of "GRPE: Relative Positional Encoding for Graph Transformer"☆58Updated 2 years ago
- ☆31Updated last year
- A library for subgraph GNN based on pyg☆41Updated 6 months ago
- Edge-Augmented Graph Transformer☆77Updated last year
- Graph Positional and Structural Encoder☆50Updated 4 months ago
- [ICML 2024] Recurrent Distance Filtering for Graph Representation Learning☆15Updated 11 months ago
- Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering☆12Updated last year
- This repository contains PyTorch implementation of the following paper: "Order Matters: Probabilistic Modeling of Node Sequence for Graph…☆28Updated this week
- ☆13Updated 2 years ago
- Official repository for the paper "On Evaluation Metrics for Graph Generative Models"☆25Updated 3 years ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆13Updated 11 months ago
- [NeurIPS'21] Higher-order Transformers for sets, graphs, and hypergraphs, in PyTorch☆68Updated 2 years ago
- ☆22Updated 11 months ago
- Implementation of the Paper "Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning" by Robin Winter, Fran…☆42Updated 2 years ago
- [ECCV'22] Equivariant Hypergraph Neural Networks, in PyTorch☆30Updated 2 years ago
- Official Pytorch implementation of NeuralWalker☆33Updated last year
- Code for the ICLR 2019 paper "Invariant and Equiovariant Graph Networks"☆24Updated 5 years ago
- Code for GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts☆16Updated 5 months ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆157Updated last year
- Source code for the paper 'Uncovering Neural Scaling Laws in Molecular Representation Learning' (NeurIPS 2023 Datasets and Benchmarks).☆14Updated last year
- Official implementation of the ICML 2022 paper "Going Deeper into Permutation-Sensitive Graph Neural Networks"☆27Updated 2 years ago
- [NeurIPS'23 Spotlight] Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance (LPS), in PyTorch☆29Updated last year
- Code for "Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs" (NeurIPS 2020)☆18Updated 4 years ago