Python library to train neural networks with a strong focus on hydrological applications.
This package has been used extensively in research over the last year and was used in various academic publications.
The core idea of this package is modularity in all places to allow easy integration of new datasets, new model
architectures or any training related aspects (e.g. loss functions, optimizer, regularization).
One of the core concepts of this code base are configuration files, which lets anyone train neural networks without
touching the code itself. The NeuralHydrology package is build on top of the deep learning framework
Pytorch, since it has proven to be the most flexible and useful for research purposes.
We (AI for Earth Science group at Institute for Machine Learning, Johannes Kepler University, Linz, Austria) are using this code in our day-to-day research and will continue to integrate our new research findings into this public repository.
Note: We will gradually add more examples/documentation over the next couple of days/weeks.
- Documentation: neuralhydrology.readthedocs.io
- Research Blog: neuralhydrology.github.io
- Bug reports/Feature requests https://github.com/neuralhydrology/neuralhydrology/issues
If you have any questions regarding the usage of this repository, feature requests or comments, please open an issue. You can also reach out to Frederik Kratzert (kratzert(at)ml.jku.at) by email.