85 citations · 302 across the 30 of their papers we have counts for
6 papers · 1 filter
Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator
Jonghyeon Lee, Boumediene Hamzi, Boya Hou +3
The Koopman operator provides a linear framework to study nonlinear dynamical systems. Its spectra offer valuable insights into system dynamics, but the operator can exhibit both d…
Gaussian Processes simplify differential equations
Jonghyeon Lee, Boumediene Hamzi, Yannis Kevrekidis +1
In this paper we use Gaussian processes (kernel methods) to learn mappings between trajectories of distinct differential equations. Our goal is to simplify both the representation…
Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach
Daniel Lengyel, Panos Parpas, Boumediene Hamzi +1
This paper examines the application of the Kernel Sum of Squares (KSOS) method for enhancing kernel learning from data, particularly in the context of dynamical systems. Traditiona…
Data-driven cold starting of good reservoirs
Lyudmila Grigoryeva, Boumediene Hamzi, Felix P. Kemeth +4
Using short histories of observations from a dynamical system, a workflow for the post-training initialization of reservoir computing systems is described. This strategy is called…
Exploring simplicity bias in 1D dynamical systems
Kamaludin Dingle, Mohammad Alaskandarani, Boumediene Hamzi +1
Arguments inspired by algorithmic information theory predict an inverse relation between the probability and complexity of output patterns in a wide range of input-output maps. Thi…
Simplicity bias, algorithmic probability, and the random logistic map
Boumediene Hamzi, Kamaludin Dingle
Simplicity bias is an intriguing phenomenon prevalent in various input-output maps, characterized by a preference for simpler, more regular, or symmetric outputs. Notably, these ma…