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aqml

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therapeutics/aqml

Amons-based quantum machine learning for quantum chemistry

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Therapeutics
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
active-learning · cheminformatics · kernel-ridge-regression · machine-learning · molecular-representation · multi-fidelity-krr · quantum-chemistry · training-set-selection
Regulatory
unknown
built by · 1

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.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • aqmecheminformatics · quantum-chemistry

    Automated Quantum Mechanical Environments (AQME) offers transparent and reproducible workflows available for Jupyter Notebooks and command lines, including: 1) RDKit- and CREST-based conformer…

  • cmilescheminformatics · quantum-chemistry

    Generate canonical molecule identifiers for quantum chemistry database

  • psikitcheminformatics · quantum-chemistry

    psi4+RDKit

  • qmllibcheminformatics · quantum-chemistry

    Quantum machine learning (QML) molecular representations and core functions

  • bofireactive-learning · cheminformatics

    Experimental design and (multi-objective) bayesian optimization.

  • deepchemquantum-chemistry

    Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

sources
  1. api.github.com/repos/binghuang2018/aqml
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2025-11-04, 26 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 →

machine-readable

/v1/entries/22.json→ .entries["aqml"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.