46 citations · 123 across the 20 of their papers we have counts for
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Micro-Macro Consistency in Multiscale Modeling: Score-Based Model Assisted Sampling of Fast/Slow Dynamical Systems
Ellis R. Crabtree, Juan M. Bello-Rivas, Ioannis G. Kevrekidis
A valuable step in the modeling of multiscale dynamical systems in fields such as computational chemistry, biology, materials science and more, is the representative sampling of th…
Tipping Points of Evolving Epidemiological Networks: Machine Learning-Assisted, Data-Driven Effective Modeling
Nikolaos Evangelou, Tianqi Cui, Juan M. Bello-Rivas +2
We study the tipping point collective dynamics of an adaptive susceptible-infected-susceptible (SIS) epidemiological network in a data-driven, machine learning-assisted manner. We…
Locating saddle points using gradient extremals on manifolds adaptively revealed as point clouds
A. Georgiou, H. Vandecasteele, J. M. Bello-Rivas +1
Steady states are invaluable in the study of dynamical systems. High-dimensional dynamical systems, due to a separation of time-scales, often evolve towards a lower dimensional man…
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points
Gianluca Fabiani, Nikolaos Evangelou, Tianqi Cui +4
We present a machine learning (ML)-assisted framework bridging manifold learning, neural networks, Gaussian processes, and Equation-Free multiscale modeling, for (a) detecting tipp…
Identifying Equivalent Training Dynamics
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova +3
Study of the nonlinear evolution deep neural network (DNN) parameters undergo during training has uncovered regimes of distinct dynamical behavior. While a detailed understanding o…
Gentlest ascent dynamics on manifolds defined by adaptively sampled point-clouds
Juan M. Bello-Rivas, Anastasia Georgiou, Hannes Vandecasteele +1
Finding saddle points of dynamical systems is an important problem in practical applications such as the study of rare events of molecular systems. Gentlest ascent dynamics (GAD) i…