Speaker
Dr
Ramses J. Sanchez
(Lamarr Institute, University of Bonn)
Description
Hybrid Machine Learning is all about inferring structured representations from empirical data, where by representations I mean transformed views of the data that make it more interpretable, or more usable for modelling and prediction. In this talk I will discuss how one can use neural networks to infer representations that satisfy partial differential equations, which one assumes model the physical processes underlying the empirical data; (ii) how simulation data from our theoretical models can be leveraged to encode mappings between infinite dimensional spaces; and (iii) how all these ideas open the door to new paradigms for scientific discovery.
