Elisabeth Roesch
Elisabeth Rösch did her undergraduate studies in Munich, Germany, (B.Sc. Bioinformatics - Technical University Munich and Ludwig-Maximilans-Univerisity Munich) and postgraduate studies in London, UK, (M.Sc. Bioinformatics and Theoretical Systems Biology- Imperial College London). Currently she is doing her PhD in the Maths and Stats department of the University of Melbourne, Australia. She focuses her research on the combination of machine learning and mechanistic modelling applied to Theoretical Systems Biology.
Session
Neural Ordinary Differential Equations (neural ODEs) are a brand new and exciting method to model nonlinear transformations as they combine the two fields of machine learning and differential equations. In this talk we discuss DiffEqFlux.jl, a package for designing and training neural ODEs, and we introduce new methodologies to improve the efficiency and robustness of neural ODEs fitting.