1 citations · 1 across the 2 of their papers we have counts for
5 papers
Online Estimation of the Koopman Operator Using Fourier Features
Tahiya Salam, Alice Kate Li, M. Ani Hsieh
Transfer operators offer linear representations and global, physically meaningful features of nonlinear dynamical systems. Discovering transfer operators, such as the Koopman opera…
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
Kong Yao Chee, M. Ani Hsieh, Nikolai Matni
Nonlinear model predictive control (MPC) is a flexible and increasingly popular framework used to synthesize feedback control strategies that can satisfy both state and control inp…
NODEO: A Neural Ordinary Differential Equation Based Optimization Framework for Deformable Image Registration
Yifan Wu, Tom Z. Jiahao, Jiancong Wang +3
Deformable image registration (DIR), aiming to find spatial correspondence between images, is one of the most critical problems in the domain of medical image analysis. In this pap…
Knowledge-Based Learning of Nonlinear Dynamics and Chaos
Tom Z. Jiahao, M. Ani Hsieh, Eric Forgoston
Extracting predictive models from nonlinear systems is a central task in scientific machine learning. One key problem is the reconciliation between modern data-driven approaches an…
A dynamic connectome supports the emergence of stable computational function of neural circuits through reward-based learning
David Kappel, Robert Legenstein, Stefan Habenschuss +2
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown…