Staying the course: iteratively locating equilibria of dynamical systems on Riemannian manifolds defined by point-clouds

Author:

Bello-Rivas Juan M.,Georgiou Anastasia,Guckenheimer John,Kevrekidis Ioannis G.

Funder

DARPA

U.S. Department of Energy

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Chemistry

Reference74 articles.

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3. D.J. Wales, Exploring Energy Landscapes. Annual Review of Physical Chemistry 69(1), 401–425 (2018). https://doi.org/10.1146/annurev-physchem-050317-021219

4. Y. LeCun, S. Chopra, R. Hadsell, M.A. Ranzato, F.J. Huang, A Tutorial on Energy-Based Learning, in Predicting Structured Data. ed. by G. Bakir, T. Hofman, B. Schölkopf, A. Smola, B. Taskar (MIT Press, Cambridge, MA, USA, 2006)

5. R. Pascanu, Y.N. Dauphin, S. Ganguli, Y. Bengio, On the Saddle Point Problem for Non-Convex Optimization. arXiv:1405.4604 (2014)

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1. Locating saddle points using gradient extremals on manifolds adaptively revealed as point clouds;Chaos: An Interdisciplinary Journal of Nonlinear Science;2023-12-01

2. Gentlest Ascent Dynamics on Manifolds Defined by Adaptively Sampled Point-Clouds;The Journal of Physical Chemistry B;2023-06-06

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