Kevin Carlberg

37 papers A* 2Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating scientific discovery with the common task framework. CoRR J. Nathan Kutz, Peter W. Battaglia, Michael P. Brenner, Kevin Carlberg, Aric A. Hagberg, Shirley Ho, Stephan Hoyer, Henning Lange, Hod Lipson, Michael W. Mahoney, Frank Noé, Max Welling, Laure Zanna, Francis Zhu, Steven L. Brunton
2025	J	`jnl`	Benchmarking Egocentric Multimodal Goal Inference for Assistive Wearable Agents. CoRR Vijay Veerabadran, Fanyi Xiao, Nitin Kamra, Pedro Matias, Joy Chen, Caley Drooff, Brett D. Roads, Riley Williams, Ethan Henderson, Xuanyi Zhao, Kevin Carlberg, Joseph Tighe, Karl Ridgeway
2025	J	`jnl`	DigiData: Training and Evaluating General-Purpose Mobile Control Agents. CoRR Yuxuan Sun, Manchen Wang, Shengyi Qian, William R. Wong, Eric Gan, Pierluca D'Oro, Alejandro Castillejo Munoz, Sneha Silwal, Pedro Matias, Nitin Kamra, Satwik Kottur, Nick Raines, Xuanyi Zhao, Joy Chen, Joseph Greer, Andrea Madotto, Allen Bolourchi, James Valori, Kevin Carlberg, Karl Ridgeway, Joseph Tighe
2024	J	`jnl`	Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need. CoRR Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Carlberg, Neil Walton, Kody J. H. Law
2023	A*	`conf`	LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields. SIGGRAPH Asia Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun
2023	J	`jnl`	LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields. CoRR Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun
2023	J	`jnl`	Model reduction for the material point method via an implicit neural representation of the deformation map. J. Comput. Phys. Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg
2023	A*	`conf`	Neural Stress Fields for Reduced-order Elastoplasticity and Fracture. SIGGRAPH Asia Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen
2023	J	`jnl`	Neural Stress Fields for Reduced-order Elastoplasticity and Fracture. CoRR Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen
2022	J	`jnl`	CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations. CoRR Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G. A. Pershing, Henrique Teles Maia, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun
2022	J	`jnl`	Learning a Visually Grounded Memory Assistant. CoRR Meera Hahn, Kevin Carlberg, Ruta Desai, James Hillis
2022	J	`jnl`	Preconditioned Least-Squares Petrov-Galerkin Reduced Order Models. CoRR Payton Lindsay, Jeffrey Fike, Irina Tezaur, Kevin Carlberg
2021	—	`conf`	Model Reduction for the Material Point Method on Nonlinear Manifolds Using Deep Learning. AAAI Spring Symposium: MLPS Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg
2021	J	`jnl`	Model reduction for the material point method via learning the deformation map and its spatial-temporal gradients. CoRR Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg
2020	J	`jnl`	Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction. CoRR Chi Hoang, Youngsoo Choi, Kevin Carlberg
2020	J	`jnl`	Optimal Assistance for Object-Rearrangement Tasks in Augmented Reality. CoRR Benjamin Newman, Kevin Carlberg, Ruta Desai
2019	J	`jnl`	Data-Driven Time Parallelism via Forecasting. SIAM J. Sci. Comput. Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
2019	J	`jnl`	Space-Time Least-Squares Petrov-Galerkin Projection for Nonlinear Model Reduction. SIAM J. Sci. Comput. Youngsoo Choi, Kevin Carlberg
2019	J	`jnl`	Statistical closure modeling for reduced-order models of stationary systems by the ROMES method. CoRR Stefano Pagani, Andrea Manzoni, Kevin Carlberg
2019	J	`jnl`	The network uncertainty quantification method for propagating uncertainties in component-based systems. CoRR Kevin Carlberg, Sofia Guzzetti, Mohammad Khalil, Khachik Sargsyan
2018	J	`jnl`	Conservative model reduction for finite-volume models. J. Comput. Phys. Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan
2018	J	`jnl`	Model reduction of dynamical systems on nonlinear manifolds using deep convolutional autoencoders. CoRR Kookjin Lee, Kevin Carlberg
2018	J	`jnl`	Stochastic Least-Squares Petrov-Galerkin Method for Parameterized Linear Systems. SIAM/ASA J. Uncertain. Quantification Kookjin Lee, Kevin Carlberg, Howard C. Elman
2017	J	`jnl`	Conservative model reduction for finite-volume models. CoRR Kevin Carlberg, Youngsoo Choi, Syuzanna Sargsyan
2017	J	`jnl`	Error estimation for surrogate models of dynamical systems using machine learning. CoRR Sumeet Trehan, Kevin Carlberg, Louis J. Durlofsky
2017	J	`jnl`	Galerkin v. least-squares Petrov-Galerkin projection in nonlinear model reduction. J. Comput. Phys. Kevin Carlberg, Matthew B. Jones, Harbir Antil
2017	J	`jnl`	Space-time least-squares Petrov-Galerkin projection for nonlinear model reduction. CoRR Youngsoo Choi, Kevin Carlberg
2016	J	`jnl`	Data-driven time parallelism via forecasting. CoRR Kevin Carlberg, Lukas Brencher, Bernard Haasdonk, Andrea Barth
2016	J	`jnl`	Krylov-Subspace Recycling via the POD-Augmented Conjugate-Gradient Method. SIAM J. Matrix Anal. Appl. Kevin Carlberg, Virginia Forstall, Ray Tuminaro
2015	J	`jnl`	Galerkin v. discrete-optimal projection in nonlinear model reduction. CoRR Kevin Carlberg, Matthew F. Barone, Harbir Antil
2015	J	`jnl`	Preserving Lagrangian Structure in Nonlinear Model Reduction with Application to Structural Dynamics. SIAM J. Sci. Comput. Kevin Carlberg, Ray S. Tuminaro, Paul T. Boggs
2015	J	`jnl`	The ROMES Method for Statistical Modeling of Reduced-Order-Model Error. SIAM/ASA J. Uncertain. Quantification Martin Drohmann, Kevin Carlberg
2014	J	`jnl`	Adaptive $h$-refinement for reduced-order models. CoRR Kevin Carlberg
2014	J	`jnl`	Preserving Lagrangian structure in nonlinear model reduction with application to structural dynamics. CoRR Kevin Carlberg, Ray Tuminaro, Paul T. Boggs
2014	J	`jnl`	The ROMES method for statistical modeling of reduced-order-model error. CoRR Martin Drohmann, Kevin Carlberg
2013	J	`jnl`	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. Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem
2013	J	`jnl`	The GNAT method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows. J. Comput. Phys. Kevin Carlberg, Charbel Farhat, Julien Cortial, David Amsallem