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Nature Communications
|
November 28, 2025
SINDy-RL for interpretable and efficient model-based reinforcement learning
Nicholas Zolman, Christian Lagemann, Urban Fasel, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
September 15, 2018
Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data
Thomas L Mohren, Thomas L Daniel, Steven L Brunton, et al.
Plos One
|
November 19, 2019
Randomized methods to characterize large-scale vortical flow networks
Zhe Bai, N Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, et al.
Physical Review. E
|
June 19, 2026
Signature of glassy dynamics in dynamic mode decompositions
Zachary G Nicolaou, Hangjun Cho, Yuanzhao Zhang, et al.
Frontiers in Artificial Intelligence
|
March 18, 2021
Discovery of Physics From Data: Universal Laws and Discrepancies
Brian M de Silva, David M Higdon, Steven L Brunton, et al.
Nature Communications
|
June 1, 2017
Chaos as an intermittently forced linear system
Steven L Brunton, Bingni W Brunton, Joshua L Proctor, et al.
Plos One
|
November 15, 2018
Development and validation of warning system of ventricular tachyarrhythmia in patients with heart failure with heart rate variability data
Wan-Tai M Au-Yeung, Per G Reinhall, Gust H Bardy, et al.
Physical Review. E
|
October 3, 2019
Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems
Shanwu Li, Eurika Kaiser, Shujin Laima, et al.
Nature Communications
|
February 16, 2021
Learning dominant physical processes with data-driven balance models
Jared L Callaham, James V Koch, Bingni W Brunton, et al.
Hardwarex
|
August 28, 2023
The experimental multi-arm pendulum on a cart: A benchmark system for chaos, learning, and control
Kadierdan Kaheman, Urban Fasel, Jason J Bramburger, et al.
Page
of 5
Search research articles
Search
Showing results (31-40 of 50) with videos related to
Sort By:
Page
of 5
Nature Communications
|
November 28, 2025
SINDy-RL for interpretable and efficient model-based reinforcement learning
Nicholas Zolman, Christian Lagemann, Urban Fasel, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
September 15, 2018
Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data
Thomas L Mohren, Thomas L Daniel, Steven L Brunton, et al.
Plos One
|
November 19, 2019
Randomized methods to characterize large-scale vortical flow networks
Zhe Bai, N Benjamin Erichson, Muralikrishnan Gopalakrishnan Meena, et al.
Physical Review. E
|
June 19, 2026
Signature of glassy dynamics in dynamic mode decompositions
Zachary G Nicolaou, Hangjun Cho, Yuanzhao Zhang, et al.
Frontiers in Artificial Intelligence
|
March 18, 2021
Discovery of Physics From Data: Universal Laws and Discrepancies
Brian M de Silva, David M Higdon, Steven L Brunton, et al.
Nature Communications
|
June 1, 2017
Chaos as an intermittently forced linear system
Steven L Brunton, Bingni W Brunton, Joshua L Proctor, et al.
Plos One
|
November 15, 2018
Development and validation of warning system of ventricular tachyarrhythmia in patients with heart failure with heart rate variability data
Wan-Tai M Au-Yeung, Per G Reinhall, Gust H Bardy, et al.
Physical Review. E
|
October 3, 2019
Discovering time-varying aerodynamics of a prototype bridge by sparse identification of nonlinear dynamical systems
Shanwu Li, Eurika Kaiser, Shujin Laima, et al.
Nature Communications
|
February 16, 2021
Learning dominant physical processes with data-driven balance models
Jared L Callaham, James V Koch, Bingni W Brunton, et al.
Hardwarex
|
August 28, 2023
The experimental multi-arm pendulum on a cart: A benchmark system for chaos, learning, and control
Kadierdan Kaheman, Urban Fasel, Jason J Bramburger, et al.
Page
of 5