Robert J. Webber

According to our database, Robert J. Webber authored at least 17 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

XTrace: Making the Most of Every Sample in Stochastic Trace Estimation.

Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

SIAM J. Matrix Anal. Appl., March, 2024

Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky.

Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

CoRR, 2024

Dynamical mixture modeling with fast, automatic determination of Markov chains.

Christopher E. Miles, Robert J. Webber

CoRR, 2024

The fast committor machine: Interpretable prediction with kernels.

David Aristoff, M. Johnson, G. Simpson, Robert J. Webber

CoRR, 2024

2023

Randomly sparsified Richardson iteration is really fast.

Jonathan Weare, Robert J. Webber

CoRR, 2023

Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications.

Joel A. Tropp, Robert J. Webber

CoRR, 2023

Robust, randomized preconditioning for kernel ridge regression.

Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber

CoRR, 2023

Localized covariance estimation: A Bayesian perspective.

Robert J. Webber, Matthias Morzfeld

CoRR, 2023

2022

Approximating Matrix Eigenvalues by Subspace Iteration with Repeated Random Sparsification.

Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare

SIAM J. Sci. Comput., 2022

Understanding and eliminating spurious modes in variational Monte Carlo using collective variables.

Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare

CoRR, 2022

Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.

Yifan Chen, Ethan N. Epperly, Joel A. Tropp, Robert J. Webber

CoRR, 2022

Weighted ensemble: Recent mathematical developments.

David Aristoff, J. Copperman, Gideon Simpson, Robert J. Webber, Daniel M. Zuckerman

CoRR, 2022

2021

Error Bounds for Dynamical Spectral Estimation.

Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare

SIAM J. Math. Data Sci., 2021

Ensemble sampler for infinite-dimensional inverse problems.

Jeremie Coullon, Robert J. Webber

Stat. Comput., 2021

Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo.

Robert J. Webber, Michael Lindsey

CoRR, 2021

Approximating matrix eigenvalues by randomized subspace iteration.

Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare

CoRR, 2021

2020

A splitting method to reduce MCMC variance.

Robert J. Webber, David Aristoff, Gideon Simpson

CoRR, 2020