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2020 – today
- 2023
[i6]Thomas M. Bury, Daniel Dylewsky, Chris T. Bauch, Madhur Anand, Leon Glass, Alvin Shrier, Gil Bub:
Predicting discrete-time bifurcations with deep learning. CoRR abs/2303.09669 (2023)- 2022
- [j2]Daniel Dylewsky
, David Barajas-Solano, Tong Ma, Alexandre M. Tartakovsky, J. Nathan Kutz:
Stochastically Forced Ensemble Dynamic Mode Decomposition for Forecasting and Analysis of Near-Periodic Systems. IEEE Access 10: 33440-33448 (2022) - [i5]Daniel Dylewsky, Timothy M. Lenton, Marten Scheffer, Thomas M. Bury, Christopher G. Fletcher, Madhur Anand, Chris T. Bauch:
Universal Early Warning Signals of Phase Transitions in Climate Systems. CoRR abs/2206.00060 (2022) - 2020
- [i4]Daniel Dylewsky, Eurika Kaiser, Steven L. Brunton, J. Nathan Kutz:
Principal Component Trajectories (PCT): Nonlinear dynamics as a superposition of time-delayed periodic orbits. CoRR abs/2005.14321 (2020) - [i3]Jason J. Bramburger, Daniel Dylewsky, J. Nathan Kutz:
Sparse Identification of Slow Timescale Dynamics. CoRR abs/2006.00940 (2020) - [i2]Daniel Dylewsky, David Barajas-Solano, Tong Ma, Alexandre M. Tartakovsky, J. Nathan Kutz:
Dynamic mode decomposition for forecasting and analysis of power grid load data. CoRR abs/2010.04248 (2020)
2010 – 2019
- 2019
- [j1]Daniel Dylewsky, Xiu Yang, Alexandre M. Tartakovsky, J. Nathan Kutz:
Engineering structural robustness in power grid networks susceptible to community desynchronization. Appl. Netw. Sci. 4(1): 24:1-24:14 (2019) - [i1]Daniel Dylewsky, Molei Tao, J. Nathan Kutz:
Data-driven multiscale decompositions for forecasting and model discovery. CoRR abs/1903.12480 (2019)
Coauthor Index
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