Machine-Learning Optimized Measurements of Chaotic Dynamical Systems via the Information Bottleneck-Reference-Cited by-同舟云学术

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Machine-Learning Optimized Measurements of Chaotic Dynamical Systems via the Information Bottleneck

Published:2024-05-10 Issue:19 Volume:132 Page:
ISSN:0031-9007
Container-title:Physical Review Letters
language:en
Short-container-title:Phys. Rev. Lett.

Author:

Murphy Kieran A.¹^ORCID,Bassett Dani S.¹²³

Affiliation:

1. Department of Bioengineering, School of Engineering and Applied Science

2. Department of Electrical and Systems Engineering, School of Engineering and Applied Science; Department of Neurology and Department of Psychiatry, Perelman School of Medicine; Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA

3. The Santa Fe Institute, Santa Fe, New Mexico 87501, USA

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevLett.132.197201/fulltext

Reference74 articles.

1. Strange Attractors, Chaotic Behavior, and Information Flow

2. Ergodic theory of chaos and strange attractors

3. Uncertainty in weather and climate prediction

4. Evidence of Chaos in Electroencephalogram Signatures of Human Performance: A Systematic Review

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Partial Information Decomposition: Redundancy as Information Bottleneck;Entropy;2024-06-26

2. Machine-Learning Optimized Measurements of Chaotic Dynamical Systems via the Information Bottleneck;Physical Review Letters;2024-05-10

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