Quantification of Uncertainties in Neural Networks (QUiNN) is a python library centered around various probabilistic wrappers over PyTorch modules in order to provide uncertainty estimation in Neural Network (NN) predictions.
Build the library
./build.sh
or
./setup.py build; setup.py install
Requirements
numpy, scipy, matplotlib, pytorch
Examples
examples/ex_fit.py
examples/ex_fit_2d.py
examples/ex_ufit.py <method> # where method=mcmc, ens or vi.
Authors
Khachik Sargsyan
Javier Murgoitio-Esandi
Oscar Diaz-Ibarra
Acknowledgements
This work is supported by
- U.S. Department of Energy, Office of Fusion Energy Sciences (OFES) under Field Work Proposal Number 20-023149.
- Laboratory Directed Research and Development (LDRD) program of Sandia National Laboratories.
1 maintainer
Metadata
1 maintainer
Release files for uqinn 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| uqinn-1.0.0.tar.gz | 55.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| uqinn-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 124.7 kB
Release files / uqinn-1.0.0.tar.gz
| Download URL | uqinn-1.0.0.tar.gz |
|---|---|
| Size | 55.6 kB |
| Tags | Source |
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Release files / uqinn-1.0.0-py3-none-any.whl
| Download URL | uqinn-1.0.0-py3-none-any.whl |
|---|---|
| Size | 69.2 kB |
| Tags | Python 3 |
|
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