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Sebastian Kaltenbach

Generative Learning of the Solution of Parametric Partial Differential Equations Using Guided Diffusion Models and Virtual Observations

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Jul 31, 2024
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A Learnable Prior Improves Inverse Tumor Growth Modeling

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Mar 07, 2024
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Generative Learning for Forecasting the Dynamics of Complex Systems

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Feb 27, 2024
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Closure Discovery for Coarse-Grained Partial Differential Equations using Multi-Agent Reinforcement Learning

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Feb 01, 2024
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Interpretable learning of effective dynamics for multiscale systems

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Sep 11, 2023
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Interpretable reduced-order modeling with time-scale separation

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Mar 03, 2023
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Semi-supervised Invertible DeepONets for Bayesian Inverse Problems

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Sep 08, 2022
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Physics-enhanced Neural Networks in the Small Data Regime

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Nov 19, 2021
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Physics-aware, deep probabilistic modeling of multiscale dynamics in the Small Data regime

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Feb 09, 2021
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Physics-aware, probabilistic model order reduction with guaranteed stability

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Jan 14, 2021
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