| bowenliu16/rl_graph_generation |
216 |
|
0 |
0 |
about 5 years ago |
0 |
|
7 |
bsd-3-clause |
Python |
| wengong-jin/hgraph2graph |
151 |
|
0 |
0 |
over 4 years ago |
0 |
|
20 |
mit |
Python |
| Hierarchical Generation of Molecular Graphs using Structural Motifs |
| BenevolentAI/guacamol_baselines |
117 |
|
0 |
0 |
over 2 years ago |
0 |
|
8 |
mit |
Python |
| Baselines models for GuacaMol benchmarks |
| zjunlp/Mol-Instructions |
116 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| Mol-Instructions is a Large-Scale Biomolecules Instruction Dataset for Large Language Models. |
| wengong-jin/multiobj-rationale |
98 |
|
0 |
0 |
over 3 years ago |
0 |
|
6 |
mit |
Python |
| Multi-Objective Molecule Generation using Interpretable Substructures (ICML 2020) |
| zjunlp/MolGen |
64 |
|
0 |
0 |
about 2 years ago |
0 |
|
0 |
mit |
Python |
| Code and pre-trained models for the paper "Domain-Agnostic Molecular Generation with Self-feedback." |
| Gananath/DrugAI |
56 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
|
Python |
| Generation and Classification of Drug Like molecule usings Neural Networks |
| aspuru-guzik-group/GA |
41 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
|
Python |
| Code for the paper: Augmenting genetic algorithms with deep neural networks for exploring the chemical space |
| compsciencelab/ligdream |
34 |
|
0 |
0 |
about 6 years ago |
0 |
|
2 |
agpl-3.0 |
Jupyter Notebook |
| Novel molecules from a reference shape! |
| dariagrechishnikova/molecule_structure_generation |
15 |
|
0 |
0 |
over 4 years ago |
0 |
|
0 |
|
Jupyter Notebook |
