icsg3d
importedtherapeutics/icsg3d
3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning (JCIM 2020)
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
- Repository
- github.com/by256/icsg3d
- Documentation
- unknown
- Tags
- cheminformatics · computational-chemistry · computational-physics · crystallography · deep-learning · representation-learning
- 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.
- biosimspacecomputational-chemistry · computational-physics
An interoperable Python framework for biomolecular simulation.
- equiformer_v2computational-chemistry · computational-physics
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
- IANNcomputational-chemistry · computational-physics
IANN (InterAtomic Neural Network Framework) is an equivariant interatomic neural network potential framework package
- ChemSharpcheminformatics · crystallography
Library for processing of chemistry related files (aiming at spectroscopy and structural files)
- Molecular3DLengthDescriptorscheminformatics · crystallography
A 3D conformational based molecular descriptor set for use in QSPR and Machine Learning.
- hbatcrystallography
HBAT 2: A Python Package to analyse Hydrogen Bonds and Other Non-covalent Interactions in Macromolecular Structures https://hbat-web.abhishek-tiwari.com
- api.github.com/repos/by256/icsg3dretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-02-15, 41 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/32.json→ .entries["icsg3d"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.