QMLearn
Quantum Machine Learning by learning one-body reduced density matrices in the AO basis.
Contributors
- Xuecheng Shao, Lukas Paetow, Md Rajib Khan Musa, Jessica A. Martinez B. and Michele Pavanello @ PRG at Rutgers University-Newark.
- Mark E Tuckerman @ Tuckerman Research Group at NYU
Some info
Code entirely in Python leveraging PySCF and Psi4Numpy for generating GTO integrals and DFT targets. Regressions are carried out with scikit-learn or other ML tools.
1 maintainer
Metadata
1 maintainer
Release files for qmlearn 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| qmlearn-0.0.1.tar.gz | 4.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| qmlearn-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.0 MB
Release files / qmlearn-0.0.1.tar.gz
| Download URL | qmlearn-0.0.1.tar.gz |
|---|---|
| Size | 4.0 MB |
| Tags | Source |
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Release files / qmlearn-0.0.1-py3-none-any.whl
| Download URL | qmlearn-0.0.1-py3-none-any.whl |
|---|---|
| Size | 39.6 kB |
| Tags | Python 3 |
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