Wasserstein distance – cmc.deusto.eus

Neural ODE Control for Classification, Approximation and Transport

data classification, deep learning, Neural ODEs, Optimal Transport, simultaneous control, transport equations, universal approximation, Wasserstein distance

D. Ruiz-Balet, E. Zuazua (2023)Neural ODE Control for Classification, Approximation and Transport, SIAM Review, Vol. 65, No. 3, pp. 735-773, https://doi.org/10.1137/21M1411433 Abstract. We analyze Neural Ordinary Differential Equations (NODEs) from…

Neural ODE Control for Classification, Approximation and Transport

Turnpike in optimal control and beyond: a survey

Large-time asymptotics for hyperbolic systems with non-symmetric relaxation: An algorithmic approach

Pointwise constraints for scalar conservation laws with positive wave velocity

Gaussian Beam ansatz for finite difference wave equations

Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics