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Andrew Pomerance

Showing results (1-10 of 9) with videos related to

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Physical 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 Pomerance
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 12, 2012
Stability of Boolean networks with generalized canalizing rulesAndrew Pomerance, Michelle Girvan, Ed Ott
Chaos (Woodbury, N.Y.)|July 28, 2025
Locality blended next-generation reservoir computing for attention accuracyDaniel J Gauthier, Andrew Pomerance, Erik Bollt
Chaos (Woodbury, N.Y.)|January 3, 2020
Forecasting chaotic systems with very low connectivity reservoir computersAaron Griffith, Andrew Pomerance, Daniel J Gauthier
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 13, 2014
Stability of Boolean networks: the joint effects of topology and update rulesShane Squires, Andrew Pomerance, Michelle Girvan, et al.
Proceedings of the National Academy of Sciences of the United States of America|May 7, 2009
The effect of network topology on the stability of discrete state models of genetic controlAndrew Pomerance, Edward Ott, Michelle Girvan, et al.
Chaos (Woodbury, N.Y.)|April 3, 2021
Using machine learning to predict statistical properties of non-stationary dynamical processes: System climate,regime transitions, and the effect of stochasticityDhruvit Patel, Daniel Canaday, Michelle Girvan, 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.)|June 4, 2020
Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systemsAlexander Wikner, Jaideep Pathak, Brian Hunt, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Physical 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 Pomerance
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 12, 2012
Stability of Boolean networks with generalized canalizing rulesAndrew Pomerance, Michelle Girvan, Ed Ott
Chaos (Woodbury, N.Y.)|July 28, 2025
Locality blended next-generation reservoir computing for attention accuracyDaniel J Gauthier, Andrew Pomerance, Erik Bollt
Chaos (Woodbury, N.Y.)|January 3, 2020
Forecasting chaotic systems with very low connectivity reservoir computersAaron Griffith, Andrew Pomerance, Daniel J Gauthier
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 13, 2014
Stability of Boolean networks: the joint effects of topology and update rulesShane Squires, Andrew Pomerance, Michelle Girvan, et al.
Proceedings of the National Academy of Sciences of the United States of America|May 7, 2009
The effect of network topology on the stability of discrete state models of genetic controlAndrew Pomerance, Edward Ott, Michelle Girvan, et al.
Chaos (Woodbury, N.Y.)|April 3, 2021
Using machine learning to predict statistical properties of non-stationary dynamical processes: System climate,regime transitions, and the effect of stochasticityDhruvit Patel, Daniel Canaday, Michelle Girvan, 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.)|June 4, 2020
Combining machine learning with knowledge-based modeling for scalable forecasting and subgrid-scale closure of large, complex, spatiotemporal systemsAlexander Wikner, Jaideep Pathak, Brian Hunt, et al.
Pageof 1