gasteigerjo / dimenetLinks
DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules" (NeurIPS-W 2020)
☆350Updated 2 years ago
Alternatives and similar repositories for dimenet
Users that are interested in dimenet are comparing it to the libraries listed below
Sorting:
- GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆215Updated 2 years ago
- Training neural network potentials☆463Updated last week
- SchNet - a deep learning architecture for quantum chemistry☆282Updated 7 years ago
- Hierarchical Generation of Molecular Graphs using Structural Motifs☆419Updated 3 years ago
- Neural Network Force Field based on PyTorch☆284Updated 5 months ago
- ☆410Updated 3 years ago
- ☆523Updated 3 years ago
- Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)☆279Updated last year
- Quantum deep field for molecule☆226Updated 4 years ago
- An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]☆355Updated last year
- GEOM: Energy-annotated molecular conformations☆239Updated 3 years ago
- [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations☆319Updated 11 months ago
- G-SchNet - a generative model for 3d molecular structures☆145Updated 2 years ago
- [ICLR 2023 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs☆268Updated 11 months ago
- ☆171Updated 3 years ago
- MoFlow: an invertible flow model for generating molecular graphs☆146Updated 2 years ago
- Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch☆519Updated last year
- Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)☆542Updated 3 years ago
- Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).☆172Updated 4 years ago
- The code of a graph neural network (GNN) for molecules, which is based on learning representations of r-radius subgraphs (i.e., fingerpri…☆331Updated 5 years ago
- ATOM3D: tasks on molecules in three dimensions☆318Updated 2 years ago
- Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).☆399Updated 2 years ago
- Literature of deep learning for graphs in Chemistry and Biology☆202Updated 5 years ago
- ☆548Updated 3 years ago
- Multi-Objective Molecule Generation using Interpretable Substructures (ICML 2020)☆165Updated 3 years ago
- The official implementation of the Molecule Attention Transformer.☆251Updated 5 years ago
- A repository of update in molecular dynamics field by recent progress in machine learning and deep learning.☆325Updated last week
- Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.☆172Updated 2 years ago
- Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.☆314Updated 2 years ago
- FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of pr…☆172Updated 3 years ago