Jonas Latz
Cited by
Cited by
Multilevel Sequential² Monte Carlo for Bayesian inverse problems
J Latz, I Papaioannou, E Ullmann
Journal of Computational Physics 368, 154-178, 2018
On the well-posedness of Bayesian inverse problems
J Latz
SIAM/ASA Journal on Uncertainty Quantification 8 (1), 451-482, 2020
Fast sampling of parameterised Gaussian random fields
J Latz, M Eisenberger, E Ullmann
Computer Methods in Applied Mechanics and Engineering 348, 978-1012, 2019
Multilevel sequential importance sampling for rare event estimation
F Wagner, J Latz, I Papaioannou, E Ullmann
SIAM Journal on Scientific Computing 42 (4), A2062-A2087, 2020
Bayesian Parameter Identification in Cahn--Hilliard Models for Biological Growth
C Kahle, KF Lam, J Latz, E Ullmann
SIAM/ASA Journal on Uncertainty Quantification 7 (2), 526-552, 2019
Analysis of Stochastic Gradient Descent in Continuous Time
J Latz
Statistics and Computing 31, 39, 2021
Classification and image processing with a semi-discrete scheme for fidelity forced Allen--Cahn on graphs
J Budd, Y van Gennip, J Latz
GAMM-Mitteilungen 44 (1), e202100004, 2021
Multilevel adaptive sparse Leja approximations for Bayesian inverse problems
IG Farcas, J Latz, E Ullmann, T Neckel, HJ Bungartz
SIAM Journal on Scientific Computing 42 (1), A424-A451, 2020
Generalized parallel tempering on Bayesian inverse problems
J Latz, JP Madrigal-Cianci, F Nobile, R Tempone
Statistics and Computing 31 (5), 1-26, 2021
Bayes Linear Methods for Inverse Problems
J Latz
Master’s thesis, University of Warwick, 2016
Bayesian inference with subset simulation in varying dimensions applied to the Karhunen–Loève expansion
F Uribe, I Papaioannou, J Latz, W Betz, E Ullmann, D Straub
International Journal for Numerical Methods in Engineering 122 (18), 5100-5127, 2021
Error analysis for probabilities of rare events with approximate models
F Wagner, J Latz, I Papaioannou, E Ullmann
SIAM Journal on Numerical Analysis 59 (4), 1948-1975, 2021
Bayesian model inference od random fields represented with the karahunen-loéve expansion
F Uribe, I Papaiannou, W Betz, J Latz, D Straub
UNCECOMP 2017 2 nd ECCOMAS Thematic Conference on Uncertainty Quantification …, 2017
Gradient flows and randomised thresholding: sparse inversion and classification
J Latz
Inverse Problems 38, 124006, 2022
A Continuous-time Stochastic Gradient Descent Method for Continuous Data
K Jin, J Latz, C Liu, CB Schönlieb
arXiv preprint arXiv:2112.03754, 2021
Certified and fast computations with shallow covariance kernels
D Kressner, J Latz, S Massei, E Ullmann
Foundations of Data Science 2 (4), 487-512, 2020
A practical example for the non-linear Bayesian filtering of model parameters
M Bulté, J Latz, E Ullmann
Quantification of Uncertainty: Improving Efficiency and Technology, 241-272, 2020
Losing momentum in continuous-time stochastic optimisation
K Jin, J Latz, C Liu, A Scagliotti
arXiv preprint arXiv:2209.03705, 2022
Solving inverse problems with Bayes' theorem
J Latz, B Sprungk
Mathematisches Forschungsinstitut Oberwolfach, 2022
Joint reconstruction-segmentation on graphs
J Budd, Y van Gennip, J Latz, S Parisotto, CB Schönlieb
arXiv preprint arXiv:2208.05834, 2022
The system can't perform the operation now. Try again later.
Articles 1–20