| deepmodeling/deepmd-kit |
1,303 |
|
0 |
2 |
about 2 years ago |
44 |
October 27, 2023 |
44 |
lgpl-3.0 |
C++ |
| A deep learning package for many-body potential energy representation and molecular dynamics |
| atomistic-machine-learning/schnetpack |
688 |
|
1 |
3 |
about 2 years ago |
10 |
September 29, 2023 |
3 |
other |
Python |
| SchNetPack - Deep Neural Networks for Atomistic Systems |
| mir-group/nequip |
478 |
|
0 |
0 |
over 2 years ago |
2 |
June 21, 2022 |
17 |
mit |
Python |
| NequIP is a code for building E(3)-equivariant interatomic potentials |
| atomicarchitects/equiformer_v2 |
318 |
|
0 |
0 |
about 1 year ago |
0 |
|
7 |
mit |
Python |
| [ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations |
| mir-group/allegro |
169 |
|
0 |
0 |
almost 3 years ago |
12 |
December 23, 2025 |
0 |
mit |
Python |
| Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials |
| msmbuilder/vde |
161 |
|
0 |
0 |
almost 4 years ago |
0 |
|
5 |
mit |
Jupyter Notebook |
| Variational Autoencoder for Dimensionality Reduction of Time-Series |
| Thinklab-SJTU/awesome-molecular-docking |
66 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
|
| We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks. |
| ncfrey/litmatter |
55 |
|
0 |
0 |
over 2 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Rapid experimentation and scaling of deep learning models on molecular and crystal graphs. |
| txie-93/gdynet |
47 |
|
0 |
0 |
over 4 years ago |
0 |
|
1 |
mit |
Jupyter Notebook |
| Unsupervised learning of atomic scale dynamics from molecular dynamics. |
| thorben-frank/mlff |
42 |
|
0 |
0 |
about 2 years ago |
0 |
|
4 |
mit |
Python |
| Build neural networks for machine learning force fields with JAX |
