I agree that this site is using cookies. You can find further informations here.
X
Bardsley, Johnathan M.
~ 300  results:
Search for persons X
?
1

A Hybrid Gibbs Sampler for Edge-Preserving Tomographic Reco..:

Uribe, Felipe ; Bardsley, Johnathan M. ; Dong, Yiqiu..
SIAM/ASA Journal on Uncertainty Quantification.  10 (2022)  3 - p. 1293-1320 , 2022
Link: https://doi.org/10.1137/..
 
?
2

Matlab Software for Supervised Habitat Mapping of Freshwate..:

Bardsley, Johnathan M. ; Howard, Marylesa ; Lorang, Mark
Remote Sensing.  13 (2021)  23 - p. 4906 , 2021
Link: https://doi.org/10.3390/..
 
?
3

Optimization-Based Markov Chain Monte Carlo Methods for Non..:

Bardsley, Johnathan M. ; Cui, Tiangang
SIAM/ASA Journal on Uncertainty Quantification.  9 (2021)  1 - p. 29-64 , 2021
Link: https://doi.org/10.1137/..
 
?
4

Scalable Optimization-Based Sampling on Function Space:

Bardsley, Johnathan M. ; Cui, Tiangang ; Marzouk, Youssef M..
SIAM Journal on Scientific Computing.  42 (2020)  2 - p. A1317-A1347 , 2020
Link: https://doi.org/10.1137/..
 
?
5

MCMC Algorithms for Computational UQ of Nonnegativity Const..:

Bardsley, Johnathan M. ; Hansen, Per Christian
SIAM Journal on Scientific Computing.  42 (2020)  2 - p. A1269-A1288 , 2020
Link: https://doi.org/10.1137/..
 
?
6

A Metropolis-Hastings-Within-Gibbs Sampler for Nonlinear Hi..:

, In: 2017 MATRIX Annals; MATRIX Book Series,
Bardsley, Johnathan M. ; Cui, Tiangang - p. 3-12 , 2019
Link: https://doi.org/10.1007/..
 
?
7

A Matrix Theoretic Derivation of the Kalman Filter:

, In: 2017 MATRIX Annals; MATRIX Book Series,
Bardsley, Johnathan M. - p. 505-513 , 2019
Link: https://doi.org/10.1007/..
 
?
8

Parameter and Uncertainty Estimation for Dynamical Systems ..:

Chung, Matthias ; Binois, Mickaël ; Gramacy, Robert B....
SIAM Journal on Scientific Computing.  41 (2019)  4 - p. A2212-A2238 , 2019
Link: https://doi.org/10.1137/..
 
?
9

Point Spread Function Estimation in X-Ray Imaging with Part..:

Joyce, Kevin T. ; Bardsley, Johnathan M. ; Luttman, Aaron
SIAM Journal on Scientific Computing.  40 (2018)  3 - p. B766-B787 , 2018
Link: https://doi.org/10.1137/..
 
?
10

Bayesian Inverse Problems with $l_1$ Priors: A Randomize-Th..:

Wang, Zheng ; Bardsley, Johnathan M. ; Solonen, Antti..
SIAM Journal on Scientific Computing.  39 (2017)  5 - p. S140-S166 , 2017
Link: https://doi.org/10.1137/..
 
?
11

Randomize-Then-Optimize for Sampling and Uncertainty Quanti..:

Bardsley, Johnathan M. ; Seppänen, Aku ; Solonen, Antti..
SIAM/ASA Journal on Uncertainty Quantification.  3 (2015)  1 - p. 1136-1158 , 2015
Link: https://doi.org/10.1137/..
 
?
12

Dealing with boundary artifacts in MCMC-based deconvolution:

Bardsley, Johnathan M. ; Luttman, Aaron
Linear Algebra and its Applications.  473 (2015)  - p. 339-358 , 2015
Link: https://doi.org/10.1016/..
 
?
13

Analysis of the Gibbs Sampler for Hierarchical Inverse Prob..:

Agapiou, Sergios ; Bardsley, Johnathan M. ; Papaspiliopoulos, Omiros.
SIAM/ASA Journal on Uncertainty Quantification.  2 (2014)  1 - p. 511-544 , 2014
Link: https://doi.org/10.1137/..
 
?
14

Randomize-Then-Optimize: A Method for Sampling from Posteri..:

Bardsley, Johnathan M. ; Solonen, Antti ; Haario, Heikki.
SIAM Journal on Scientific Computing.  36 (2014)  4 - p. A1895-A1910 , 2014
Link: https://doi.org/10.1137/..
 
?
15

MCMC-Based Image Reconstruction with Uncertainty Quantifica..:

Bardsley, Johnathan M.
SIAM Journal on Scientific Computing.  34 (2012)  3 - p. A1316-A1332 , 2012
Link: https://doi.org/10.1137/..
 
1-15