most citedLeveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators
Showing math.OCShow all

2 papers · 1 filter

math.OC2024★ 1 cited

A time-dependent symplectic network for non-convex path planning problems with linear and nonlinear dynamics

Zhen Zhang, Chenye Wang, Shanqing Liu +2

We propose a novel neural network architecture (TSympOCNet) to address high--dimensional optimal control problems with linear and nonlinear dynamics. An important application of th…

math.OC2021

Efficient and robust high-dimensional sparse logistic regression via nonlinear primal-dual hybrid gradient algorithms

Jérôme Darbon, Gabriel P. Langlois

Logistic regression is a widely used statistical model to describe the relationship between a binary response variable and predictor variables in data sets. It is often used in mac…