Juan M. Cardenas

12 papers A* 2Journal 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
Integration of local and global surrogates for failure probability estimation.
CoRR
Audrey Gaymann, Juan M. Cardenas, Sung Min Jo, Marco Panesi, Alireza Doostan
2024 A* conf
A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples.
ICML
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023 J jnl
A unified framework for learning with nonlinear model classes from arbitrary linear samples.
CoRR
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023 J jnl
An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains.
SIAM J. Sci. Comput.
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023 A* conf
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions.
NeurIPS
Juan M. Cardenas, Ben Adcock, Nick C. Dexter
2023 J jnl
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions.
CoRR
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2022 J jnl
A high order unfitted hybridizable discontinuous Galerkin method for linear elasticity.
CoRR
Juan M. Cardenas, Manuel E. Solano
2022 J jnl
An Adaptive sampling and domain learning strategy for multivariate function approximation on unknown domains.
CoRR
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2022 J jnl
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning.
CoRR
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2022 J jnl
Towards optimal sampling for learning sparse approximation in high dimensions.
CoRR
Ben Adcock, Juan M. Cardenas, Nick C. Dexter, Sebastian Moraga
2020 J jnl
Near-Optimal Sampling Strategies for Multivariate Function Approximation on General Domains.
SIAM J. Math. Data Sci.
Ben Adcock, Juan M. Cardenas
2019 J jnl
Optimal sampling strategies for multivariate function approximation on general domains.
CoRR
Ben Adcock, Juan M. Cardenas