MinkaiXu / GeoDiffLinks
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
☆359Updated 2 years ago
Alternatives and similar repositories for GeoDiff
Users that are interested in GeoDiff are comparing it to the libraries listed below
Sorting:
- ☆502Updated 2 years ago
- DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design☆334Updated last year
- Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)☆262Updated last year
- GEOM: Energy-annotated molecular conformations☆224Updated 3 years ago
- Geometric Latent Diffusion Models for 3D Molecule Generation☆251Updated last year
- Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure☆279Updated 2 years ago
- [ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs☆239Updated 3 months ago
- Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets☆309Updated last year
- ☆480Updated 3 years ago
- Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).☆166Updated 3 years ago
- A Euclidean diffusion model for structure-based drug design.☆421Updated 3 months ago
- MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation☆102Updated 8 months ago
- Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch☆472Updated 5 months ago
- Awesome papers related to generative molecular modeling and design.☆325Updated 5 months ago
- Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.☆281Updated last year
- The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)☆262Updated last year
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆267Updated 3 months ago
- [ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)☆211Updated 2 years ago
- Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)☆190Updated 2 years ago
- ATOM3D: tasks on molecules in three dimensions☆307Updated 2 years ago
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆168Updated last year
- Training neural network potentials☆406Updated 3 weeks ago
- DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Awa…☆322Updated last year
- Implementation for SE(3) diffusion model with application to protein backbone generation☆377Updated last year
- 💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)☆189Updated 2 years ago
- ☆209Updated last year
- GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆200Updated 2 years ago
- EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein☆508Updated 3 months ago
- FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation☆228Updated 5 months ago
- code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503☆524Updated last year