51 citations · 174 across the 11 of their papers we have counts for
11 papers
Neural models for prediction of spatially patterned phase transitions: methods and challenges
Daniel Dylewsky, Sonia Kéfi, Madhur Anand +1
Dryland vegetation ecosystems are known to be susceptible to critical transitions between alternative stable states when subjected to external forcing. Such transitions are often d…
Early Warning Signals for Bifurcations Embedded in High Dimensions
Daniel Dylewsky, Madhur Anand, Chris T. Bauch
Recent work has highlighted the utility of methods for early warning signal detection in dynamic systems approaching critical tipping thresholds. Often these tipping points resembl…
Predicting discrete-time bifurcations with deep learning
Thomas M. Bury, Daniel Dylewsky, Chris T. Bauch +4
Many natural and man-made systems are prone to critical transitions -- abrupt and potentially devastating changes in dynamics. Deep learning classifiers can provide an early warnin…
Universal Early Warning Signals of Phase Transitions in Climate Systems
Daniel Dylewsky, Timothy M. Lenton, Marten Scheffer +4
The potential for complex systems to exhibit tipping points in which an equilibrium state undergoes a sudden and often irreversible shift is well established, but prediction of the…
Stochastically forced ensemble dynamic mode decomposition for forecasting and analysis of near-periodic systems
Daniel Dylewsky, David Barajas-Solano, Tong Ma +2
Time series forecasting remains a central challenge problem in almost all scientific disciplines. We introduce a novel load forecasting method in which observed dynamics are modele…
Sparse Identification of Slow Timescale Dynamics
Jason J. Bramburger, Daniel Dylewsky, J. Nathan Kutz
Multiscale phenomena that evolve on multiple distinct timescales are prevalent throughout the sciences. It is often the case that the governing equations of the persistent and appr…