ChemFlow
importedtherapeutics/chemflow
Uncover meaningful structures of latent spaces learned by generative models with flows!
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Therapeutics
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/garywei944/ChemFlow
- Documentation
- unknown
- Tags
- ai4science · drug-discovery · machine-learning · optimal-transport
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- cMolGPTai4science · drug-discovery
GPT (Generative Pre-trained Transformer) for de novo molecular design by enforcing specified targets
- GEMGenai4science · drug-discovery
A generative model for phenotypic-based drug discovery
- KG4SLai4science · drug-discovery
Synthetic lethality (SL) is a promising gold mine for the discovery of anti-cancer drug targets. KG4SL is the first graph neural network (GNN)-based model that uses knowledge graph for SL prediction.
- molgenai4science · drug-discovery
Lightweight toolkit for de novo molecular generation: SMILES & SELFIES tokenizers, CharRNN / MolGPT / VAE models, training, sampling, and MOSES-style metrics.
- SL_benchmarkai4science · drug-discovery
Benchmarking study of machine learning methods for prediction of synthetic lethality
- Polymer-Ensemble-Similarityoptimal-transport
Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance
- api.github.com/repos/garywei944/ChemFlowretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-05-10, 47 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/44.json→ .entries["chemflow"]
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