Sebastian Kaltenbach

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 10

Top Topics

Dynamical Systems

Emission Tomography

Top Venues

J. Comput. Phys.

Publications

Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
Generative Learning for Forecasting the Dynamics of Complex Systems. CoRR (2024)
Jan-Philipp von Bassewitz, Sebastian Kaltenbach, Petros Koumoutsakos
Closure Discovery for Coarse-Grained Partial Differential Equations using Multi-Agent Reinforcement Learning. CoRR (2024)
Jonas Weidner, Ivan Ezhov, Michal Balcerak, Marie-Christin Metz, Sergey Litvinov, Sebastian Kaltenbach, Leonhard F. Feiner, Laurin Lux, Florian Kofler, Jana Lipková, Jonas Latz, Daniel Rueckert, Bjoern H. Menze, Benedikt Wiestler
A Learnable Prior Improves Inverse Tumor Growth Modeling. CoRR (2024)
Emmanuel Menier, Sebastian Kaltenbach, Mouadh Yagoubi, Marc Schoenauer, Petros Koumoutsakos
Interpretable learning of effective dynamics for multiscale systems. CoRR (2023)
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis, Petros Koumoutsakos
Interpretable reduced-order modeling with time-scale separation. CoRR (2023)
Sebastian Kaltenbach, Paris Perdikaris, Phaedon-Stelios Koutsourelakis
Semi-supervised Invertible DeepONets for Bayesian Inverse Problems. CoRR (2022)
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Physics-aware, probabilistic model order reduction with guaranteed stability. ICLR (2021)
Jonas Eichelsdörfer, Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Physics-enhanced Neural Networks in the Small Data Regime. CoRR (2021)
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Physics-aware, probabilistic model order reduction with guaranteed stability. CoRR (2021)
Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems. J. Comput. Phys. 419 (2020)