Deep Learning experiments for seasonal climate forecasting
content of the repository
-
dl4seas: modules
- IO: inputs / outputs, for now functions to create TF protobuf files from xarray datasets and a list of netcdf files
- NN: custom layers to use in CNNs and DataGenerator Class
- preprocessing: for now only a
train_scaler
function using dask-ml or scikit-learn to train a Standard Scaler on xarray Dataset objects - utils: some utility functions
notebooks, scripts, outputs and figures for the core experiments building on Convolutional Neural Networks (incl. Auto-encoders)
notebooks, scripts, outputs and figures for the experiments specifically building on pre-trained NN architectures (Transfer Learning)
notebooks, scripts, outputs and figures for the experiments building on "wide and Deep"* architectures, which include auxiliary inputs representing the current state and / or the recent evolution of the climate system from observational sources.
- Cheng, H.-T., and Coauthors, 2016: Wide & Deep Learning for Recommender Systems. arXiv:1606.07792 [cs, stat]s