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Exploring decomposition of temporal patterns to facilitate learning of neural...
This record contains data for the manuskript "Exploring decomposition of temporal patterns to facilitate learning of neural networks for ground-level daily maximum 8-hour... -
MLAir (v1.0.0) - a tool to enable fast and flexible machine learning on air d...
MLAir (Machine Learning on Air data) is an environment that simplifies and accelerates the creation of new machine learning (ML) models for the analysis and forecasting of... -
O3ResNet: A deep learning based forecast system to predict local ground-level...
This record contains data for the manuscript "O3ResNet: A deep learning based forecast system to predict local ground-level daily maximum 8-hour average ozone" by L. H. Leufen,... -
O3ResNet: A deep learning based forecast system to predict local ground-level...
This record contains data for the manuscript "O3ResNet: A deep learning based forecast system to predict local ground-level daily maximum 8-hour average ozone in rural and... -
Exploring decomposition of temporal patterns to facilitate learning of neural...
This record contains data for the manuskript "Exploring decomposition of temporal patterns to facilitate learning of neural networks for ground-level daily maximum 8-hour... -
Assessment of a subgrid-scale model for convection-dominated mass transfer fo...
Data accompanying the publication "Assessment of a subgrid-scale model for convection-dominated mass transfer for the initial transient rise of a bubble". -
Data Samples for temperature forecasting by deep learning methods
Here we provide the data samples (one-year data) to allow the users to fast test the machine learning workflow code that is published on Zenodo...
