Carlos Alberto Gómez Gonzalez
I am a Marie-Curie postdoctoral fellow at the Earth Sciences department of the Barcelona Supercomputing Center (BSC-ES) where I lead a research line on Artificial Intelligence applied to climate and atmospheric composition problems. I am interested in the development of machine and deep learning algorithms for topics, such as statistical downscaling, bias correction techniques, data-driven parameterisations, and the study of extreme climate events. Finally, I care about open science, sustainable code and reproducibility.
Talks
DL4DS - A python library for empirical downscaling and super-resolution of Earth Science data
In this talk, we present DL4DS, a python package that implements a wide variety of state-of-the-art and novel algorithms for downscaling gridded Earth Science data with deep neural networks. DL4DS has been designed with the goal of providing a general framework for convolutional neural networks with configurable architectures and training procedures to enable benchmark, comparative and ablation studies.