Nitzler, Jonas;Biehler, Jonas;Fehn, Niklas;Koutsourelakis, Phaedon-Stelios;Wall, Wolfgang A.A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulationsComputer Methods in Applied Mechanics and Engineering2022400115600
Coelho Lima, Isabela;Robens-Radermacher, Annika;Titscher, Thomas;Kadoke, Daniel;Koutsourelakis, Phaedon-Stelios;Unger, Jörg F.Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forward model’s accuracyComputational Mechanics20227061189-1210
Kaltenbach, S.;Koutsourelakis, P.Physics-Aware, Deep Probabilistic Modeling of Multiscale Dynamics in the Small Data Regime14th WCCM-ECCOMAS CongressCIMNE2021
Coelho Lima, Isabela;Robens-Radermacher, Annika;Titscher, Thomas;Kadoke, Daniel;Koutsourelakis, Phaedon-Stelios;Unger, Jörg F.Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forward model’s accuracyComputational Mechanics2022
Rixner, Maximilian;Koutsourelakis, Phaedon-SteliosSelf-supervised optimization of random material microstructures in the small-data regimenpj Computational Materials202281
Lucor, Didier;Agrawal, Atul;Sergent, AnneSimple computational strategies for more effective physics-informed neural networks modeling of turbulent natural convectionJournal of Computational Physics2022111022
Rixner, Maximilian;Koutsourelakis, Phaedon-SteliosA probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observablesJournal of Computational Physics2021110218
Kaltenbach, Sebastian;Koutsourelakis, Phaedon-SteliosIncorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systemsJournal of Computational Physics2020109673