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Recommendations for the article From Fourier to Koopman: Spectral Methods for Long-term Time Series Prediction
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
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visibility_off | Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties | Alex Troy Mallen, Henning Lange, J. Kutz | 2021-06-10 | ArXiv | 6 | 31 |
visibility_off | Temporally-Consistent Koopman Autoencoders for Forecasting Dynamical Systems | I. Nayak, Debdipta Goswami, Mrinal Kumar, Fernando L. Teixeira | 2024-03-19 | ArXiv | 0 | 8 |
visibility_off | Predictive Nonlinear Modeling by Koopman Mode Decomposition | Akira Kusaba, Kilho Shin, D. Shepard, T. Kuboyama | 2020-11-01 | 2020 International Conference on Data Mining Workshops (ICDMW) | 0 | 13 |
visibility_off | Koopman Operator Framework for Time Series Modeling and Analysis | A. Surana | 2018-01-09 | Journal of Nonlinear Science | 35 | 24 |
visibility_off | Koopman Operator Framework for Time Series Modeling and Analysis | A. Surana | 2018-01-09 | Journal of Nonlinear Science | 35 | 24 |
visibility_off | Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies | Tomoharu Iwata, Y. Kawahara | 2022-12-26 | ArXiv | 0 | 30 |
visibility_off | High-dimensional time series prediction using kernel-based Koopman mode regression | Jia-Chen Hua, Farzad Noorian, Duncan J. M. Moss, P. Leong, G. Gunaratne | 2017-09-15 | Nonlinear Dynamics | 25 | 37 |
visibility_off | Forecasting Sequential Data using Consistent Koopman Autoencoders | Omri Azencot, N. Benjamin Erichson, Vanessa Lin, Michael W. Mahoney | 2020-03-04 | ArXiv | 108 | 64 |
visibility_off | Characterizing the load profile in power grids by Koopman mode decomposition of interconnected dynamics | A. Tavasoli, Behnaz Moradijamei, Heman Shakeri | 2023-04-16 | ArXiv | 1 | 11 |
visibility_off | Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics | Tomoharu Iwata, Y. Kawahara | 2020-12-11 | ArXiv | 9 | 30 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |