Modeling & Data Analysis
Overview: Machine learning is a growing field based on computational and statistical algorithms that are trained with experimental data to give computers the ability to learn specific tasks for prediction-making. On the other hand, data assimilation algorithms can help to forecast variables of complex systems as well as interpolate sparse observation data using knowledge a mathematical model based on observed data.
State of the art: At present, the use of neural networks for modeling and learning has rapidly increased in recent years. In addition, new training algorithms have been raising with different properties to tackle complex problems.
Our research in Machine Learning and Data Assimilation aims to: