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20192022
most citedHeavy Ball Neural Ordinary Differential Equations

15 citations · 39 across the 12 of their papers we have counts for

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9 papers · 1 filter

math.OC2022

Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme

Alexander Vidal, Samy Wu Fung, Luis Tenorio +2

A normalizing flow (NF) is a mapping that transforms a chosen probability distribution to a normal distribution. Such flows are a common technique used for data generation and dens…

math.OC2022

Neural ODE Control for Trajectory Approximation of Continuity Equation

Karthik Elamvazhuthi, Bahman Gharesifard, Andrea Bertozzi +1

We consider the controllability problem for the continuity equation, corresponding to neural ordinary differential equations (ODEs), which describes how a probability measure is pu…

math.OC20229 cited

Controlling conservation laws II: compressible Navier-Stokes equations

Wuchen Li, Siting Liu, Stanley Osher

We propose, study, and compute solutions to a class of optimal control problems for hyperbolic systems of conservation laws and their viscous regularization. We take barotropic com…

math.OC2021

A Fast Proximal Gradient Method and Convergence Analysis for Dynamic Mean Field Planning

Jiajia Yu, Rongjie Lai, Wuchen Li +1

In this paper, we propose an efficient and flexible algorithm to solve dynamic mean-field planning problems based on an accelerated proximal gradient method. Besides an easy-to-imp…

math.OC20202 cited

A mean field game inverse problem

Lisang Ding, Wuchen Li, Stanley Osher +1

Mean-field games arise in various fields including economics, engineering, and machine learning. They study strategic decision making in large populations where the individuals int…

math.OC2020

Controlling Propagation of epidemics via mean-field control

Wonjun Lee, Siting Liu, Hamidou Tembine +2

The coronavirus disease 2019 (COVID-19) pandemic is changing and impacting lives on a global scale. In this paper, we introduce a mean-field game model in controlling the propagati…