chaitjo / geometric-gnn-dojoLinks
Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks (ICML 2023)
☆508Updated last year
Alternatives and similar repositories for geometric-gnn-dojo
Users that are interested in geometric-gnn-dojo are comparing it to the libraries listed below
Sorting:
- Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch☆499Updated 9 months ago
- ☆499Updated 3 years ago
- Message Passing Neural Networks for Simplicial and Cell Complexes☆164Updated 2 years ago
- ☆176Updated 2 years ago
- A curated list of topological deep learning (TDL) resources and links.☆265Updated 2 weeks ago
- Graphium: Scaling molecular GNNs to infinity.☆235Updated 4 months ago
- Computing on Topological Domains☆241Updated last week
- Topological Deep Learning☆292Updated last week
- All graph/GNN papers accepted at NeurIPS 2024.☆83Updated 10 months ago
- TopoBench is a Python library designed to standardize benchmarking and accelerate research in Topological Deep Learning☆184Updated last week
- Advanced Topics in Artificial Intelligence, NUS CS6208, 2023☆327Updated 2 years ago
- A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)☆124Updated last year
- SignNet and BasisNet☆101Updated 2 years ago
- Exphormer: Sparse Transformer for Graphs☆187Updated last year
- code for the paper "DiGress: Discrete Denoising diffusion for graph generation"☆458Updated 6 months ago
- Graph Neural PDEs☆335Updated 2 years ago
- ☆531Updated 3 years ago
- Deep learning for molecules and materials book☆673Updated this week
- A modular framework for neural networks with Euclidean symmetry☆1,155Updated 3 weeks ago
- Equivariant Subgraph Aggregation Networks (ICLR 2022 Spotlight)☆89Updated 2 years ago
- Recipe for a General, Powerful, Scalable Graph Transformer☆783Updated last year
- Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).☆382Updated 2 years ago
- code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503☆544Updated 2 years ago
- A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks☆138Updated 3 years ago
- DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…☆339Updated 2 years ago
- Topological Graph Neural Networks (ICLR 2022)☆122Updated 3 years ago
- All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.☆223Updated 10 months ago
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆41Updated 7 months ago
- Training neural network potentials☆437Updated 2 weeks ago
- GFlowNet library specialized for graph & molecular data☆271Updated 3 months ago