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Science Advances|July 17, 2026
Tailored forecasting from short time series via meta-learningDeclan A Norton, Edward Ott, Andrew Pomerance, et al.Chaos (Woodbury, N.Y.)|July 9, 2021
Using data assimilation to train a hybrid forecast system that combines machine-learning and knowledge-based componentsAlexander Wikner, Jaideep Pathak, Brian R Hunt, et al.Neural Networks : the Official Journal of the International Neural Network Society|November 17, 2023
Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computingAlexander Wikner, Joseph Harvey, Michelle Girvan, et al.Chaos (Woodbury, N.Y.)|January 8, 2020
Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based modelJaideep Pathak, Alexander Wikner, Rebeckah Fussell, et al.Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 13, 2002
Phase synchronization of chaotic attractors in the presence of two competing periodic signalsRomulus Breban, Edward OttChaos (Woodbury, N.Y.)|April 1, 2019
Observing microscopic transitions from macroscopic bursts: Instability-mediated resetting in the incoherent regime of the D-dimensional generalized Kuramoto modelSarthak Chandra, Edward OttPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 13, 2009
Approximating the largest eigenvalue of the modified adjacency matrix of networks with heterogeneous node biasesEdward Ott, Andrew PomeranceChaos (Woodbury, N.Y.)|June 5, 2003
Stalactite basin structure of dynamical systems with transient chaos in an invariant manifoldVasily Dronov, Edward OttPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|March 5, 2009
Using synchronism of chaos for adaptive learning of time-evolving network topologyFrancesco Sorrentino, Edward OttPageof 14