Robert J. Webber

25 papers Journal 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Everything is Vecchia: Unifying low-rank and sparse inverse Cholesky approximations.
CoRR
Eagan Kaminetz, Robert J. Webber
2026 J jnl
Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop.
CoRR
Noah Amsel, Yves Baumann, Paul Beckman, Peter Bürgisser, Chris Camaño, Tyler Chen, Edmond Chow, Anil Damle, Michal Derezinski, Mark Embree, Ethan N. Epperly, Robert D. Falgout, Mark Fornace, Anne Greenbaum, Chen Greif, Diana Halikias, Zhen Huang, Elias Jarlebring, Yiannis Koutis, Daniel Kressner, Rasmus Kyng, Jörg Liesen, Jackie Lok, Raphael A. Meyer, Yuji Nakatsukasa, Kate Pearce, Richard Peng, David Persson, Elizaveta Rebrova, Ryan Schneider, Rikhav Shah, Edgar Solomonik, Nikhil Srivastava, Alex Townsend, Robert J. Webber, Jess Williams
2026 J jnl
Variational Markov chain mixtures with automatic component selection.
Stat. Comput.
Christopher E. Miles, Robert J. Webber
2025 J jnl
Embrace Rejection: Kernel Matrix Approximation by Accelerated Randomly Pivoted Cholesky.
SIAM J. Matrix Anal. Appl.
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2025 J jnl
Keep the beat going: Automatic drum transcription with momentum.
CoRR
Alisha L. Foster, Robert J. Webber
2024 J jnl
Dynamical mixture modeling with fast, automatic determination of Markov chains.
CoRR
Christopher E. Miles, Robert J. Webber
2024 J jnl
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky.
CoRR
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2024 J jnl
Randomized Kaczmarz with tail averaging.
CoRR
Ethan N. Epperly, Gil Goldshlager, Robert J. Webber
2024 J jnl
The fast committor machine: Interpretable prediction with kernels.
CoRR
David Aristoff, M. Johnson, G. Simpson, Robert J. Webber
2024 J jnl
XTrace: Making the Most of Every Sample in Stochastic Trace Estimation.
SIAM J. Matrix Anal. Appl.
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2023 J jnl
Localized covariance estimation: A Bayesian perspective.
CoRR
Robert J. Webber, Matthias Morzfeld
2023 J jnl
Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications.
CoRR
Joel A. Tropp, Robert J. Webber
2023 J jnl
Randomly sparsified Richardson iteration is really fast.
CoRR
Jonathan Weare, Robert J. Webber
2023 J jnl
Robust, randomized preconditioning for kernel ridge regression.
CoRR
Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber
2023 J jnl
XTrace: Making the most of every sample in stochastic trace estimation.
CoRR
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2022 J jnl
Approximating Matrix Eigenvalues by Subspace Iteration with Repeated Random Sparsification.
SIAM J. Sci. Comput.
Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare
2022 J jnl
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations.
CoRR
Yifan Chen, Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
2022 J jnl
Understanding and eliminating spurious modes in variational Monte Carlo using collective variables.
CoRR
Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare
2022 J jnl
Weighted ensemble: Recent mathematical developments.
CoRR
David Aristoff, J. Copperman, Gideon Simpson, Robert J. Webber, Daniel M. Zuckerman
2021 J jnl
Approximating matrix eigenvalues by randomized subspace iteration.
CoRR
Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare
2021 J jnl
Ensemble sampler for infinite-dimensional inverse problems.
Stat. Comput.
Jeremie Coullon, Robert J. Webber
2021 J jnl
Error Bounds for Dynamical Spectral Estimation.
SIAM J. Math. Data Sci.
Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare
2021 J jnl
Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo.
CoRR
Robert J. Webber, Michael Lindsey
2020 J jnl
A splitting method to reduce MCMC variance.
CoRR
Robert J. Webber, David Aristoff, Gideon Simpson
2020 J jnl
Error bounds for dynamical spectral estimation.
CoRR
Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare