Lecture

Learning Chemical Reaction Networks

Description

This lecture covers the sparse learning of chemical reaction networks from trajectory data, focusing on data-based methods for dynamical systems, forward and backward problems, and learning approaches using basis functions and log-likelihood functions. The instructor presents theoretical results and tools, along with numerical examples of predator-prey systems and intracellular viral infections.

Official source

https://mediaspace.epfl.ch/media/0_dx56rkj7

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Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Statistics

Statistical inference: Mathematical statistics

Systems science and engineering

Systems theory: Chaos theory

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