Python library to train neural networks with a strong focus on hydrological applications. This package has been used extensively in research over the last years 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 let anyone train neural networks without touching the code itself. The NeuralHydrology package is built on top of the deep learning framework PyTorch, since it has proven to be the most flexible and useful for research purposes. We (the AI for Earth Science g...
NeuroDiffEq is a Python package built with PyTorch that uses artificial neural networks (ANNs) to so...
Building artificial neural networks and machine learning models in Python with PyTorch and TensorFlo
Artificial Neural Networks (ANNs) trained on specific cognitive tasks have re-emerged as a useful to...
This codebase implements NeuralHydrology modeling code used in the following paper: Nearing, G. S., ...
This zenodo archive contains the library code used to run the experiments in Gauch et al., "Rainfall...
As of recent times, neural networks have drawn in a lot of attention and popularity because of their...
Machine learning has shown great promise for simulating hydrological phenomena. However, the develop...
This Research Topic of Frontiers in Neuroinformatics is dedicated to the memory of Rolf Kötter (1961...
For around a decade, deep learning — the sub-field of machine learning that refers to artificial ne...
The Python programming language is steadily increasing in popularity as the language of choice for s...
The Python programming language is steadily increasing in popularity as the language of choice for s...
This is the second book in Deep Learning models series by the author. Deep learning models are widel...
This book contains practical implementations of several deep learning projects in multiple domains, ...
International audienceReservoirPy is a simple user-friendly library based on Python scientific modul...
This package provides a python framework for building and testing machine learning models for time s...
NeuroDiffEq is a Python package built with PyTorch that uses artificial neural networks (ANNs) to so...
Building artificial neural networks and machine learning models in Python with PyTorch and TensorFlo
Artificial Neural Networks (ANNs) trained on specific cognitive tasks have re-emerged as a useful to...
This codebase implements NeuralHydrology modeling code used in the following paper: Nearing, G. S., ...
This zenodo archive contains the library code used to run the experiments in Gauch et al., "Rainfall...
As of recent times, neural networks have drawn in a lot of attention and popularity because of their...
Machine learning has shown great promise for simulating hydrological phenomena. However, the develop...
This Research Topic of Frontiers in Neuroinformatics is dedicated to the memory of Rolf Kötter (1961...
For around a decade, deep learning — the sub-field of machine learning that refers to artificial ne...
The Python programming language is steadily increasing in popularity as the language of choice for s...
The Python programming language is steadily increasing in popularity as the language of choice for s...
This is the second book in Deep Learning models series by the author. Deep learning models are widel...
This book contains practical implementations of several deep learning projects in multiple domains, ...
International audienceReservoirPy is a simple user-friendly library based on Python scientific modul...
This package provides a python framework for building and testing machine learning models for time s...
NeuroDiffEq is a Python package built with PyTorch that uses artificial neural networks (ANNs) to so...
Building artificial neural networks and machine learning models in Python with PyTorch and TensorFlo
Artificial Neural Networks (ANNs) trained on specific cognitive tasks have re-emerged as a useful to...