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Adam Rupe
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Koopman operator and its approximations for systems with symmetries
A Salova, J Emenheiser, A Rupe, JP Crutchfield, RM D’Souza
Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (9), 2019
402019
Local causal states and discrete coherent structures
A Rupe, JP Crutchfield
Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (7), 2018
262018
DisCo: Physics-based unsupervised discovery of coherent structures in spatiotemporal systems
A Rupe, N Kumar, V Epifanov, K Kashinath, O Pavlyk, F Schlimbach, ...
2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing …, 2019
172019
Nonequilibrium statistical mechanics and optimal prediction of partially-observed complex systems
A Rupe, VV Vesselinov, JP Crutchfield
New Journal of Physics 24 (10), 103033, 2022
102022
Spacetime symmetries, invariant sets, and additive subdynamics of cellular automata
A Rupe, JP Crutchfield
arXiv preprint arXiv:1812.11597, 2018
52018
Algebraic theory of patterns as generalized symmetries
A Rupe, JP Crutchfield
Symmetry 14 (8), 1636, 2022
42022
Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources
VV Vesselinov, D O'Malley, LP Frash, B Ahmmed, AT Rupe, S Karra, ...
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2021
42021
Towards unsupervised segmentation of extreme weather events
A Rupe, K Kashinath, N Kumar, V Lee, JP Crutchfield
arXiv preprint arXiv:1909.07520, 2019
42019
Spacetime autoencoders using local causal states
A Rupe, JP Crutchfield
arXiv preprint arXiv:2010.05451, 2020
22020
Properties of Koopman operator and its approximations for dynamical systems with symmetries.
A Salova, J Emenheiser, A Rupe, R D'Souza, J Crutchfield
Bulletin of the American Physical Society 63, 2018
22018
Transfer Operator Framework for Earth System Predictability and Water Cycle Extremes
A Rupe, VV Vesselinov, B Nadiga, D DeSantis, M Anghel
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2021
12021
Deep Learning Recognizes Climate and Weather Patterns and Emulates Complex Processes Critical to the Modeling of Earth's Climate
K Kashinath, M Prabhat, M Mudigonda, A Mahesh, S Kim, J Wu, A Albert, ...
99th American Meteorological Society Annual Meeting, 2019
12019
A physics-based approach to unsupervised discovery of coherent structures in spatiotemporal systems
A Rupe, JP Crutchfield, K Kashinath
arXiv preprint arXiv:1709.03184, 2017
12017
On Principles of Emergent Organization
AT Rupe, JP Crutchfield
arXiv preprint arXiv:2311.13749, 2023
2023
Physics-Informed Representation Learning for Emergent Organization in Complex Dynamical Systems
A Rupe, K Kashinath, N Kumar, JP Crutchfield
arXiv preprint arXiv:2304.12586, 2023
2023
Reduced-order modeling of Arctic Amplification feedbacks
A Rupe, C Bakker, D Desantis, J Lu
APS March Meeting Abstracts 2023, W53. 007, 2023
2023
Unsupervised Extreme Weather Segmentation
A Rupe, K Kashinath, N Kumar, JP Crutchfield
AGU Fall Meeting Abstracts 2022, A36B-08, 2022
2022
Koopman Theory and Predictive Equivalence: Learning Implicit Models of Complex Systems from Partial Observations
A Rupe, V Vesselinov, J Crutchfield
APS March Meeting Abstracts 2022, N09. 004, 2022
2022
Discovering emergent organization in complex spatiotemporal systems
A Rupe, K Kashinath, J Crutchfield
AGU Fall Meeting Abstracts 2021, NG52A-01, 2021
2021
The Search For Thermodynamic Principles of Organization [Slides]
AT Rupe
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2021
2021
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Artiklar 1–20