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Physics-enhanced Neural Networks in the Small Data Regime
Jonas Eichelsdörfer, Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Identifying the dynamics of physical systems requires a machine learning model that can assimilate observational data, but also incorporate the laws of physics. Neural Networks bas…
Self-supervised optimization of random material microstructures in the small-data regime
Maximilian Rixner, Phaedon-Stelios Koutsourelakis
While the forward and backward modeling of the process-structure-property chain has received a lot of attention from the materials community, fewer efforts have taken into consider…
Physics-aware, deep probabilistic modeling of multiscale dynamics in the Small Data regime
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
The data-based discovery of effective, coarse-grained (CG) models of high-dimensional dynamical systems presents a unique challenge in computational physics and particularly in the…
Physics-aware, probabilistic model order reduction with guaranteed stability
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Given (small amounts of) time-series' data from a high-dimensional, fine-grained, multiscale dynamical system, we propose a generative framework for learning an effective, lower-di…