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2020 – today
- 2024
[j4]Ethan N. Epperly
, Joel A. Tropp, Robert J. Webber:
XTrace: Making the Most of Every Sample in Stochastic Trace Estimation. SIAM J. Matrix Anal. Appl. 45(1): 1-23 (2024)- [i16]David Aristoff, M. Johnson, G. Simpson, Robert J. Webber:
The fast committor machine: Interpretable prediction with kernels. CoRR abs/2405.10410 (2024) - [i15]Christopher E. Miles, Robert J. Webber:
Dynamical mixture modeling with fast, automatic determination of Markov chains. CoRR abs/2406.04653 (2024) - [i14]Ethan N. Epperly, Joel A. Tropp, Robert J. Webber:
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky. CoRR abs/2410.03969 (2024) - [i13]Ethan N. Epperly, Gil Goldshlager, Robert J. Webber:
Randomized Kaczmarz with tail averaging. CoRR abs/2411.19877 (2024) - 2023
- [i12]Robert J. Webber, Matthias Morzfeld:
Localized covariance estimation: A Bayesian perspective. CoRR abs/2301.04828 (2023) - [i11]Ethan N. Epperly, Joel A. Tropp, Robert J. Webber:
XTrace: Making the most of every sample in stochastic trace estimation. CoRR abs/2301.07825 (2023) - [i10]Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber:
Robust, randomized preconditioning for kernel ridge regression. CoRR abs/2304.12465 (2023) - [i9]Joel A. Tropp, Robert J. Webber:
Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications. CoRR abs/2306.12418 (2023) - [i8]Jonathan Weare, Robert J. Webber:
Randomly sparsified Richardson iteration is really fast. CoRR abs/2309.17270 (2023) - 2022
- [j3]Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare:
Approximating Matrix Eigenvalues by Subspace Iteration with Repeated Random Sparsification. SIAM J. Sci. Comput. 44(5): 3067- (2022) - [i7]David Aristoff, J. Copperman, Gideon Simpson, Robert J. Webber, Daniel M. Zuckerman:
Weighted ensemble: Recent mathematical developments. CoRR abs/2206.14943 (2022) - [i6]Yifan Chen, Ethan N. Epperly, Joel A. Tropp, Robert J. Webber:
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations. CoRR abs/2207.06503 (2022) - [i5]Huan Zhang, Robert J. Webber, Michael Lindsey, Timothy C. Berkelbach, Jonathan Weare:
Understanding and eliminating spurious modes in variational Monte Carlo using collective variables. CoRR abs/2211.09767 (2022) - 2021
- [j2]Jeremie Coullon, Robert J. Webber:
Ensemble sampler for infinite-dimensional inverse problems. Stat. Comput. 31(3): 28 (2021) - [j1]Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare:
Error Bounds for Dynamical Spectral Estimation. SIAM J. Math. Data Sci. 3(1): 225-252 (2021) - [i4]Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach, Jonathan Weare:
Approximating matrix eigenvalues by randomized subspace iteration. CoRR abs/2103.12109 (2021) - [i3]Robert J. Webber, Michael Lindsey:
Rayleigh-Gauss-Newton optimization with enhanced sampling for variational Monte Carlo. CoRR abs/2106.10558 (2021) - 2020
- [i2]Robert J. Webber, Erik H. Thiede, Douglas Dow, Aaron R. Dinner, Jonathan Weare:
Error bounds for dynamical spectral estimation. CoRR abs/2005.02248 (2020) - [i1]Robert J. Webber, David Aristoff, Gideon Simpson:
A splitting method to reduce MCMC variance. CoRR abs/2011.13899 (2020)
Coauthor Index
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