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J. Nathan Kutz (University of Washington): Data-driven model discovery and physics-informed learning
Shenglin Huang - Data-Driven Model Discovery for Non-equilibrium Processes - IPAM at UCLA
Data Driven Discovery of Dynamical Systems and PDEs
Steve Brunton: Discovering interpretable and generalizable dynamical systems from data
DDPS | Data-driven modeling of dynamical systems: A systems theoretic perspective
Data-driven model discovery: Targeted use of deep neural networks for physics and engineering
HLCS | Interpretable and Explainable Data-Driven Methods for Physical Simulations
PySINDy tutorial 1: overview of PySINDy for sparse system identification
SIAM DS21: Igor Mezić - Koopman Operator, Geometry, and Learning of Dynamical Systems
New Book!!! Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Dr. Russ Rockne: A machine learning biology applying data driven model discovery methods
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Last Updated: September 29, 2026
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2025 USACM Novel Methods Fall Seminar Title: Talk given at the University of Washington on 6/6/19 for the Physics Informed Machine Learning Workshop. Hosted by Nathan ... This video provides a high-level overview of this new series on A major challenge in the study of Recorded 18 April 2023. Shenglin Huang of the University of Pennsylvania presents " This video highlights recent innovations in Machine Learning for Physics and the Physics of Learning 2019 Workshop III: Validation and Guarantees in Learning Physical ... Description: In this talk, we will investigate various approaches to modeling website: faculty.washington.edu/kutz This video highlights physics-informed machine learning architectures that allow for the ... Russ Rockne ( twitter.com/rrockne) presents "SA machine learning biology applying
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