| 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 | 42 | 2019 |
| Local causal states and discrete coherent structures A Rupe, JP Crutchfield Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (7), 2018 | 27 | 2018 |
| 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 | 17 | 2019 |
| 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 | 11 | 2022 |
| Spacetime symmetries, invariant sets, and additive subdynamics of cellular automata A Rupe, JP Crutchfield arXiv preprint arXiv:1812.11597, 2018 | 5 | 2018 |
| Algebraic theory of patterns as generalized symmetries A Rupe, JP Crutchfield Symmetry 14 (8), 1636, 2022 | 4 | 2022 |
| 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 | 4 | 2021 |
| Towards unsupervised segmentation of extreme weather events A Rupe, K Kashinath, N Kumar, V Lee, JP Crutchfield arXiv preprint arXiv:1909.07520, 2019 | 4 | 2019 |
| Spacetime autoencoders using local causal states A Rupe, JP Crutchfield arXiv preprint arXiv:2010.05451, 2020 | 2 | 2020 |
| 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 | 2 | 2018 |
| On principles of emergent organization A Rupe, JP Crutchfield Physics Reports 1071, 1-47, 2024 | 1 | 2024 |
| 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 | 1 | 2023 |
| 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 | 1 | 2021 |
| 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 | 1 | 2019 |
| 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 | 1 | 2017 |
| Control of an Energy Balance Model around Sea-Ice Tipping Points PM Kooloth, J Lu, CKR Bakker, D DeSantis, A Rupe AGU23, 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 |
