Grigo, Constantin;Koutsourelakis, Phaedon-Stelios
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime
Journal of Computational Physics
2019
397
108842

Grigo, Constantin;Koutsourelakis, Phaedon-Stelios
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime
Journal of Computational Physics
2019

Zhu, Yinhao;Zabaras, Nicholas;Koutsourelakis, Phaedon-Stelios;Perdikaris, Paris
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
Journal of Computational Physics
2019

Biehler, Jonas;Mäck, Markus;Nitzler, Jonas;Hanss, Michael;Koutsourelakis, Phaedon‐Stelios;Wall, Wolfgang A.
Multifidelity approaches for uncertainty quantification
GAMM-Mitteilungen
2019
e201900008

Grigo, Constantin;Koutsourelakis, Phaedon-Stelios
Bayesian Model and Dimension Reduction for Uncertainty Propagation: Applications in Random Media
SIAM/ASA Journal on Uncertainty Quantification
2019
7
1
292-323

Felsberger, Lukas;Koutsourelakis, Phaedon-Stelios
Physics-Constrained, Data-Driven Discovery of Coarse-Grained Dynamics
Communications in Computational Physics
2019
25
5

Schöberl, Markus;Zabaras, Nicholas;Koutsourelakis, Phaedon-Stelios
Predictive collective variable discovery with deep Bayesian models
The Journal of Chemical Physics
2019
150
2
024109