This repository contains the Juypter Notebooks and python files to reproduce the main results of the paper "Non-Linear Dimensionality Reduction with a Variational Encoder Decoder to Understand Convective Processes in Climate Models"
Moist convection alters the environment in two different ways: Deep convection associated with stro...
This project was targeting the development of a computational approach that would allow resolving cl...
Notebook developed to demonstrate the computational reproduction of the paper Detection and attribut...
This repository contains the Juypter Notebooks and python files to reproduce the main results of the...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learni...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in...
International audienceLinear methods of dimensionality reduction are useful tools for handling and i...
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in...
Use-case of Deep Generative Models for Perfect Prognosis Climate Downscaling.Language: Python and R....
<p>The python scripts to reproduce the computational examples presented in "A discontinuo...
University of Minnesota M.S. thesis.October 2015. Major: Computer Science. Advisor: Vipin Kumar. 1 ...
International audienceLinear dimensionality reduction techniques, notably principal component analys...
Moist convection alters the environment in two different ways: Deep convection associated with stro...
This project was targeting the development of a computational approach that would allow resolving cl...
Notebook developed to demonstrate the computational reproduction of the paper Detection and attribut...
This repository contains the Juypter Notebooks and python files to reproduce the main results of the...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learni...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Deep learning can accurately represent sub-grid-scale convective processes in climate models, learni...
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in...
International audienceLinear methods of dimensionality reduction are useful tools for handling and i...
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in...
Use-case of Deep Generative Models for Perfect Prognosis Climate Downscaling.Language: Python and R....
<p>The python scripts to reproduce the computational examples presented in "A discontinuo...
University of Minnesota M.S. thesis.October 2015. Major: Computer Science. Advisor: Vipin Kumar. 1 ...
International audienceLinear dimensionality reduction techniques, notably principal component analys...
Moist convection alters the environment in two different ways: Deep convection associated with stro...
This project was targeting the development of a computational approach that would allow resolving cl...
Notebook developed to demonstrate the computational reproduction of the paper Detection and attribut...
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