akirasosa / pytorch-dimenet
☆23Updated last year
Related projects: ⓘ
- "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…☆34Updated 4 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆65Updated 2 years ago
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆41Updated last year
- This repository contains a collection of resources and papers on GNN Models on Crystal Solid State Materials☆59Updated 3 months ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆17Updated 2 years ago
- [TMLR 2023] Training and simulating MD with ML force fields☆101Updated 2 months ago
- Data and code for graph neural network accelerated molecular dynamics☆33Updated 2 years ago
- Codebase for Cormorant Neural Networks☆59Updated 2 years ago
- Implementation of "Denoise Pretraining on Non-equilibrium Molecular Conformations for Accurate and Transferable Neural Potentials" in PyT…☆11Updated last year
- Generate and predict molecular electron densities with Euclidean Neural Networks☆40Updated 11 months ago
- Jax / Haiku implementation of DimeNet++.☆16Updated 2 years ago
- Official implementation of the NeurIPS 23 spotlight paper of ♾️InfGCN♾️.☆11Updated 9 months ago
- A DGL implementation of "Directional Message Passing for Molecular Graphs" (ICLR 2020).☆18Updated 11 months ago
- ☆27Updated 2 years ago
- ☆18Updated last year
- Implementing PaiNN in Pytorch Geometric☆12Updated 2 years ago
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆23Updated last year
- cG-SchNet - a conditional generative neural network for 3d molecular structures☆52Updated last year
- G-SchNet extension for SchNetPack☆45Updated 2 weeks ago
- ☆30Updated 4 years ago
- A graph neural network for the prediction of bond dissociation energies for molecules of any charge.☆53Updated last year
- A light-weight PyTorch extension for equivariant deep learning☆15Updated last month
- Deep learning for molecules quantum chemistry properties prediction☆35Updated 3 years ago
- Tensorflow implementation of message passing neural networks for molecules and materials☆12Updated 4 years ago
- [NeurIPS 2023] The implementation for the paper "Crystal Structure Prediction by Joint Equivariant Diffusion"☆65Updated 2 months ago
- G-SchNet - a generative model for 3d molecular structures☆129Updated last year
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆78Updated 2 years ago
- [ICLR 2024] The implementation for the paper "Space Group Constrained Crystal Generation"☆23Updated last week
- Deep Supervised Graph Partitioning Model☆14Updated 3 years ago
- Higher order equivariant graph neural networks for 3D point clouds☆33Updated last year