This dataset contains the pre-trained models from the publication "A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling". For each input configuration, the dataset contains 10 model repetitions. Each run has a separate folder, containing the model weights, run configuration, validation and test set results. The models were trained using the code available at https://github.com/kratzert/multiple_forcing Paper reference (accepted for publication): Kratzert, F., Klotz, D., Hochreiter, S., and Nearing, G. S.: A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/1...
Code used in the paper "Deep learning models for generation of precipitation maps based on NWP" Als...
Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and heav...
One of the most crucial applications of radar-based precipitation nowcasting systems is the short-te...
Abstract. A deep learning rainfall–runoff model can take multiple meteorological forcing products as...
This dataset contains the pretrained model weights and precomputed results for the paper "Thundersto...
In this repository you can find the weights of the models used in the paper "Deep Learning Approach ...
International audienceShort or mid-term rainfall forecasting is a major task with several environmen...
This page includes spatiotemporal datasets used in the paper STConvS2S: Spatiotemporal Convolutional...
Despite showing great success of applications in many commercial fields, machine learning and data s...
This data archive includes the source code of EXP-HYDRO, standard DL, hybrid-J, and hybrid-Z models,...
RainNet is a convolutional deep neural network for precipitation nowcasting. This repository contai...
The datasets used in Van Kempen et al., 2021 are included in this repository. These files consist of...
This study presents a novel application of machine learning to deliver optimised, multi-model combin...
This repository contains the source code, pre-trained models, and dataset of the paper 'Key factors ...
In this repository you can find the converted images of the RADOLAN Product provided by the German W...
Code used in the paper "Deep learning models for generation of precipitation maps based on NWP" Als...
Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and heav...
One of the most crucial applications of radar-based precipitation nowcasting systems is the short-te...
Abstract. A deep learning rainfall–runoff model can take multiple meteorological forcing products as...
This dataset contains the pretrained model weights and precomputed results for the paper "Thundersto...
In this repository you can find the weights of the models used in the paper "Deep Learning Approach ...
International audienceShort or mid-term rainfall forecasting is a major task with several environmen...
This page includes spatiotemporal datasets used in the paper STConvS2S: Spatiotemporal Convolutional...
Despite showing great success of applications in many commercial fields, machine learning and data s...
This data archive includes the source code of EXP-HYDRO, standard DL, hybrid-J, and hybrid-Z models,...
RainNet is a convolutional deep neural network for precipitation nowcasting. This repository contai...
The datasets used in Van Kempen et al., 2021 are included in this repository. These files consist of...
This study presents a novel application of machine learning to deliver optimised, multi-model combin...
This repository contains the source code, pre-trained models, and dataset of the paper 'Key factors ...
In this repository you can find the converted images of the RADOLAN Product provided by the German W...
Code used in the paper "Deep learning models for generation of precipitation maps based on NWP" Als...
Climate models (CM) are used to evaluate the impact of climate change on the risk of floods and heav...
One of the most crucial applications of radar-based precipitation nowcasting systems is the short-te...