GeoLDM
importedtherapeutics/geoldm
Geometric Latent Diffusion Models for 3D Molecule Generation
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/MinkaiXu/GeoLDM
- Documentation
- unknown
- Tags
- deep-generative-model · diffusion-models · drug-discovery · geometric-deep-learning · icml-2023 · molecule · molecule-generation
- 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.
- BInDdiffusion-models · drug-discovery · molecule-generation
Official implementation of "BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design" (Advanced Science)
- dgl-lifescidrug-discovery · geometric-deep-learning · molecule
Python package for graph neural networks in chemistry and biology
- BBARdrug-discovery · molecule-generation
Official Github for "Molecular generative model via retrosynthetically prepared chemical building block assembly" (Advanced Science)
- PhoreGendrug-discovery · molecule-generation
PhoreGen: Pharmacophore-Oriented 3D Molecular Generation towards Efficient Feature-Customized Drug Discovery https://www.nature.com/articles/s43588-025-00850-5
- PS-VAEdrug-discovery · molecule-generation
This repo contains the codes for our paper: Molecule Generation by Principal Subgraph Mining and Assembling.
- reinvent-randomizeddrug-discovery · molecule-generation
Recurrent Neural Network using randomized SMILES strings to generate molecules
- api.github.com/repos/MinkaiXu/GeoLDMretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-06-09, 274 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/37.json→ .entries["geoldm"]
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