Predicting Nonlinear and Complex Systems with Machine Learning II
FOCUS · N09 · ID: 46517
Presentations
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Choosing Optimal Reservoir Computers
ORAL · Invited
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Publication: T. L. Carroll and L. M. Pecora, "Network structure effects in reservoir computers," Chaos, vol. 29, p. 083130, Aug 2019.<br>T. L. Carroll, "Dimension of reservoir computers," Chaos, vol. 30, p. 013102, 2020.<br>T. L. Carroll, "Path length statistics in reservoir computers," Chaos:, vol. 30, p. 083130, 2020.<br>T. L. Carroll, "Do reservoir computers work best at the edge of chaos?," Chaos, vol. 30, p. 121109, Dec 2020.<br>T. L. Carroll, "Low dimensional manifolds in reservoir computers," Chaos, vol. 31, p. 043113, 2021.<br>T. L. Carroll, "Optimizing Reservoir Computers for Signal Classification," Frontiers in Physiology, vol. 12, 2021-June-18 2021.
Presenters
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Thomas L Carroll
United States Naval Research Laboratory
Authors
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Thomas L Carroll
United States Naval Research Laboratory
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Physical Reservoir Computing with Over-Moded Complex Systems
ORAL
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Publication: Shukai Ma, Thomas Antonsen, Steven Anlage, Edward Ott, "Short-wavelength Reverberant Wave Systems for Enhanced Reservoir Computing," DOI: 10.21203/rs.3.rs-783820/v1
Presenters
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Shukai Ma
University of Maryland, College Park
Authors
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Shukai Ma
University of Maryland, College Park
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Thomas M Antonsen
University of Maryland, College Park
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Steven M Anlage
University of Maryland, College Park
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Edward Ott
University of Maryland, College Park
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Data-driven Surrogate Modeling for Nonlinear Material Systems in Unconventional Computing
ORAL
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Presenters
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Benjamin Grossmann
UES, Inc
Authors
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Philip Buskohl
Air Force Research Lab - WPAFB, AFRL
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Benjamin Grossmann
UES, Inc
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Daniel Nelson
UES, Inc
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Amanda Criner
AFRL
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Timothy J Vincent
UES, Inc
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Andrew Gillman
AFRL, Air Force Research Lab - WPAFB
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Koopman Theory and Predictive Equivalence: Learning Implicit Models of Complex Systems from Partial Observations
ORAL
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Presenters
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Adam Rupe
Los Alamos National Laboratory
Authors
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Adam Rupe
Los Alamos National Laboratory
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Velimir V Vesselinov
Los Alamos National Laboratory
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James P Crutchfield
University of California, Davis
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Local Flow Environment as Information Processing Medium
ORAL
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Publication: Local Flow Environment as Information Processing Medium (planned)
Presenters
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Timothy J Vincent
UES, Inc
Authors
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Timothy J Vincent
UES, Inc
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Philip Buskohl
Air Force Research Lab - WPAFB, AFRL
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Benjamin Grossmann
UES, Inc
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Daniel Nelson
UES, Inc
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Benjamin Dickinson
AFRL
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Jeffery Baur
AFRL
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Alexander Pankonien
AFRL
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Reservoir Computing: Structure analysis and dynamics predictability
ORAL
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Publication: Follmann, R. and Rosa Jr, E., 2019. "Predicting slow and fast neuronal dynamics with machine learning". Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(11), p.113119.
Presenters
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Rosangela Follmann
Illinois State University
Authors
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Rosangela Follmann
Illinois State University
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Cassie Mcginnis
Illinois State University
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Gangadhar Katuri
Illinois State University
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Epaminondas Rosa
Illinois State University
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Learning Parametric Dynamical Systems from Videos with Integer Programming
ORAL
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Presenters
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Kazem Meidani
Carnegie Mellon University
Authors
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Kazem Meidani
Carnegie Mellon University
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Amir Barati Farimani
Carnegie Mellon University
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Bayesian Modelling of Phase-Field Crystal Models for Targeted Crystalline Patterns
ORAL
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Publication: [1] Natsuhiko Yoshinaga, Satoru Tokuda, "Bayesian Modelling of Pattern Formation from One Snapshot of Pattern", arXiv:2006.06125 (2021).
Presenters
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Natsuhiko Yoshinaga
WPI-AIMR, Tohoku Univ, Tohoku Univ
Authors
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Natsuhiko Yoshinaga
WPI-AIMR, Tohoku Univ, Tohoku Univ
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Satoru Tokuda
Research Institute for Information Technology, Kyushu University, Kasuga 816-8580, Japan
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Learning and predicting complex systems dynamics from single-variable observations
ORAL
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Presenters
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George Stepaniants
Massachusetts Institute of Technology MIT
Authors
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George Stepaniants
Massachusetts Institute of Technology MIT
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Alasdair Hastewell
Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology MI
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Dominic J Skinner
Massachusetts Institute of Technology, Massachusetts Institute of Technology MIT
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Jan F Totz
MIT, Massachusetts Institute of Technology MIT, Massachusetts Institute of Technology MI
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Jorn Dunkel
Massachusetts Institute of Technology MIT, Department of Mathematics, Massachusetts Institute of Technology, Massachusetts Institute of Technology
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The information bottleneck powered by deep learning to illuminate micro to macro relationships in complex systems
ORAL
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Presenters
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Kieran A Murphy
University of Pennsylvania
Authors
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Kieran A Murphy
University of Pennsylvania
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Danielle S Bassett
University of Pennsylvania
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Universality in Prediction Markets
ORAL
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Publication: We have a planned paper for this research.
Presenters
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Keanu M Rock
Ryerson University
Authors
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Keanu M Rock
Ryerson University
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Lotka-Volterra predator-prey lattice model with a time-dependent carrying capacity.
ORAL
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Presenters
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Mohamed Swailem
Virginia Tech
Authors
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Mohamed Swailem
Virginia Tech
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Uwe C Tauber
Virginia Tech
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Cyclic predator-prey models with time varying rates
ORAL
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Presenters
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Hana Z Mir
Virginia Tech
Authors
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Michel Pleimling
Virginia Tech
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Hana Z Mir
Virginia Tech
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James Stidham
Virginia Tech
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