Juan M. Cardenas

According to our database, Juan M. Cardenas authored at least 8 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of six.
• Erdős number of five.

2023

An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains.

Ben Adcock, Juan M. Cardenas, Nick C. Dexter

SIAM J. Sci. Comput., February, 2023

A unified framework for learning with nonlinear model classes from arbitrary linear samples.

Ben Adcock, Juan M. Cardenas, Nick C. Dexter

CoRR, 2023

CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions.

Juan M. Cardenas, Ben Adcock, Nick C. Dexter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning.

Ben Adcock, Juan M. Cardenas, Nick C. Dexter

CoRR, 2022

A high order unfitted hybridizable discontinuous Galerkin method for linear elasticity.

Juan M. Cardenas, Manuel E. Solano

CoRR, 2022

Towards optimal sampling for learning sparse approximation in high dimensions.

Ben Adcock, Juan M. Cardenas, Nick C. Dexter, Sebastian Moraga

CoRR, 2022

2020

Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains.

Ben Adcock, Juan M. Cardenas

SIAM J. Math. Data Sci., 2020

2019

Optimal sampling strategies for multivariate function approximation on general domains.

Ben Adcock, Juan M. Cardenas

CoRR, 2019