Kevin Carlberg

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 26

Top Topics

Kalman Filtering

Statistical Modeling

Top Venues

J. Comput. Phys.

SIAM J. Sci. Comput.

SIAM/ASA J. Uncertain. Quantification

Publications

Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody J. H. Law
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. CoRR (2024)
Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun
LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields. SIGGRAPH Asia (2023)
Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg
Model reduction for the material point method via an implicit neural representation of the deformation map. J. Comput. Phys. 478 (2023)
Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture. CoRR (2023)
Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture. SIGGRAPH Asia (2023)
Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun
LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields. CoRR (2023)
Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, G. A. Pershing, Henrique Teles Maia, Maurizio Chiaramonte, Kevin Carlberg, Eitan Grinspun
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations. CoRR (2022)
Payton Lindsay, Jeffrey Fike, Irina Tezaur, Kevin Carlberg
Preconditioned Least-Squares Petrov-Galerkin Reduced Order Models. CoRR (2022)
Meera Hahn, Kevin Carlberg, Ruta Desai, James Hillis
Learning a Visually Grounded Memory Assistant. CoRR (2022)
Peter Yichen Chen, Maurizio Chiaramonte, Eitan Grinspun, Kevin Carlberg
Model Reduction for the Material Point Method on Nonlinear Manifolds Using Deep Learning. AAAI Spring Symposium: MLPS (2021)
Peter Yichen Chen, Maurizio Chiaramonte, Eitan Grinspun, Kevin Carlberg
Model reduction for the material point method via learning the deformation map and its spatial-temporal gradients. CoRR (2021)
Benjamin Newman, Kevin Carlberg, Ruta Desai
Optimal Assistance for Object-Rearrangement Tasks in Augmented Reality. CoRR (2020)
Chi Hoang, Youngsoo Choi, Kevin Carlberg
Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction. CoRR (2020)
Youngsoo Choi, Kevin Carlberg
Space-Time Least-Squares Petrov-Galerkin Projection for Nonlinear Model Reduction. SIAM J. Sci. Comput. 41 (1) (2019)
Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
Data-Driven Time Parallelism via Forecasting. SIAM J. Sci. Comput. 41 (3) (2019)
Kevin Carlberg, Sofia Guzzetti, Mohammad Khalil, Khachik Sargsyan
The network uncertainty quantification method for propagating uncertainties in component-based systems. CoRR (2019)
Stefano Pagani, Andrea Manzoni, Kevin Carlberg
Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. CoRR (2019)
Kookjin Lee, Kevin Carlberg
Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders. CoRR (2018)
Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan
Conservative model reduction for finite-volume models. J. Comput. Phys. 371 (2018)
Kookjin Lee, Kevin Carlberg, Howard C. Elman
Stochastic Least-Squares Petrov-Galerkin Method for Parameterized Linear Systems. SIAM/ASA J. Uncertain. Quantification 6 (1) (2018)
Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan
Conservative model reduction for finite-volume models. CoRR (2017)
Kevin Carlberg, Matthew B. Jones, Harbir Antil
Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction. J. Comput. Phys. 330 (2017)
Youngsoo Choi, Kevin Carlberg
Space-time least-squares Petrov-Galerkin projection for nonlinear model reduction. CoRR (2017)
Sumeet Trehan, Kevin Carlberg, Louis J. Durlofsky
Error estimation for surrogate models of dynamical systems using machine learning. CoRR (2017)
Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
Data-driven time parallelism via forecasting. CoRR (2016)
Kevin Carlberg, Virginia Forstall, Ray Tuminaro
Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method. SIAM J. Matrix Anal. Appl. 37 (3) (2016)
Martin Drohmann, Kevin Carlberg
The ROMES Method for Statistical Modeling of Reduced-Order-Model Error. SIAM/ASA J. Uncertain. Quantification 3 (1) (2015)
Kevin Carlberg, Ray S. Tuminaro, Paul T. Boggs
Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics. SIAM J. Sci. Comput. 37 (2) (2015)
Kevin Carlberg, Matthew F. Barone, Harbir Antil
Galerkin v. discrete-optimal projection in nonlinear model reduction. CoRR (2015)
Kevin Carlberg
Adaptive $h$-refinement for reduced-order models. CoRR (2014)
Kevin Carlberg, Ray Tuminaro, Paul T. Boggs
Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics. CoRR (2014)
Martin Drohmann, Kevin Carlberg
The ROMES method for statistical modeling of reduced-order-model error. CoRR (2014)
Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem
Corrigendum to "The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows" [J. Comput. Physics 242 (2013) 623-647]. J. Comput. Phys. 250 (2013)
Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem
The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows. J. Comput. Phys. 242 (2013)