MinkaiXu / GeoDiff
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
☆352Updated last year
Alternatives and similar repositories for GeoDiff:
Users that are interested in GeoDiff are comparing it to the libraries listed below
- ☆477Updated 2 years ago
- DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design☆322Updated 11 months ago
- GEOM: Energy-annotated molecular conformations☆218Updated 2 years ago
- Geometric Latent Diffusion Models for 3D Molecule Generation☆236Updated last year
- Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)☆259Updated last year
- Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure☆268Updated 2 years ago
- [ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs☆233Updated last month
- A Euclidean diffusion model for structure-based drug design.☆401Updated last month
- Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).☆165Updated 3 years ago
- Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch☆454Updated 3 months ago
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆254Updated last month
- Awesome papers related to generative molecular modeling and design.☆319Updated 3 months ago
- MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generation☆98Updated 6 months ago
- The official implementation of 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction (ICLR 2023)☆244Updated last year
- ☆465Updated 3 years ago
- A geometry-complete diffusion generative model (GCDM) for 3D molecule generation and optimization (Nature CommsChem)☆193Updated 6 months ago
- Pre-training Molecular Graph Representation with 3D Geometry, ICLR'22 (https://openreview.net/forum?id=xQUe1pOKPam)☆185Updated 2 years ago
- [ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)☆208Updated last year
- Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets☆290Updated last year
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆167Updated last year
- 💊 A 3D Generative Model for Structure-Based Drug Design (NeurIPS 2021)☆187Updated 2 years ago
- Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.☆272Updated last year
- ☆200Updated 10 months ago
- ATOM3D: tasks on molecules in three dimensions☆307Updated 2 years ago
- Implementation for SE(3) diffusion model with application to protein backbone generation☆361Updated last year
- FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation☆215Updated 3 months ago
- Training neural network potentials☆386Updated 3 weeks ago
- ☆165Updated 3 years ago
- Geom3D: Geometric Modeling on 3D Structures, NeurIPS 2023☆119Updated 9 months ago
- Generative Models for Graph-Based Protein Design☆271Updated 4 years ago