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Multi-scale modeling of energetic material sensitivity requires telescoping physics from the nano- and micro- and meso-scales to ... Description: In this talk, we will investigate various approaches to modeling dynamical systems from Description: Reduced-order models are often obtained by projection onto a subspace; standard least squares in linear spaces is a ... This talk aims to close the gap by developing new theories and scalable numerical algorithms for complex dynamical systems that ... Talk Abstract World is changing very rapidly. Today we do not sell aircraft engines, but hours of flight, we do not sell an electric ...
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AI, Data Driven Models & Machine Learning
DDPS | Generative Machine Learning Approaches for Data-Driven Modeling and Reductions
DDPS | Data-driven modeling of dynamical systems: A systems theoretic perspective
DDPS | Data-driven information geometry approach to stochastic model reduction
DDPS | Towards Third Wave AI: Interpretable, Robust Trustworthy Machine Learning
DDPS | 'Probabilistic methods for data-driven reduced-order modeling'
DDPS | Empowering Hybrid Twins from Physics-Informed Artificial Intelligence
DDPS | ‘Predicting Heart Rhythm Disorders from Spatio-Temporal Imaging Data using AI'
DDPS | Data-driven learning of nonlocal models: bridging scales and design of new neural networks
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Last Updated: June 12, 2026
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