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Physics-enhanced Neural Networks in the Small Data Regime., , and . CoRR, (2021)A Learnable Prior Improves Inverse Tumor Growth Modeling., , , , , , , , , and 4 other author(s). CoRR, (2024)Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems., and . J. Comput. Phys., (2020)Closure Discovery for Coarse-Grained Partial Differential Equations using Multi-Agent Reinforcement Learning., , and . CoRR, (2024)Interpretable learning of effective dynamics for multiscale systems., , , , and . CoRR, (2023)Interpretable reduced-order modeling with time-scale separation., , and . CoRR, (2023)Generative Learning for Forecasting the Dynamics of Complex Systems., , and . CoRR, (2024)Physics-aware, probabilistic machine learning in the Small Data regime.. Technical University of Munich, Germany, (2023)Semi-supervised Invertible DeepONets for Bayesian Inverse Problems., , and . CoRR, (2022)Physics-aware, probabilistic model order reduction with guaranteed stability., and . ICLR, OpenReview.net, (2021)