Jonas Latz

According to our database, Jonas Latz authored at least 22 papers between 2018 and 2024.

Collaborative distances:

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

2024

Adaptive stepsize algorithms for Langevin dynamics.

Alix Leroy, Benedict J. Leimkühler, Jonas Latz, Desmond J. Higham

CoRR, 2024

A Learnable Prior Improves Inverse Tumor Growth Modeling.

Jonas Weidner, Ivan Ezhov, Michal Balcerak, Marie-Christin Metz, Sergey Litvinov, Sebastian Kaltenbach, Leonhard F. Feiner, Laurin Lux, Florian Kofler, Jana Lipková, Jonas Latz, Daniel Rueckert, Bjoern H. Menze, Benedikt Wiestler

CoRR, 2024

2023

Bayesian Inverse Problems Are Usually Well-Posed.

Jonas Latz

SIAM Rev., August, 2023

Joint Reconstruction-Segmentation on Graphs.

Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb

SIAM J. Imaging Sci., June, 2023

Subsampling Error in Stochastic Gradient Langevin Diffusions.

Kexin Jin, Chenguang Liu, Jonas Latz

CoRR, 2023

Subsampling in ensemble Kalman inversion.

Matei Hanu, Jonas Latz, Claudia Schillings

CoRR, 2023

Can Physics-Informed Neural Networks beat the Finite Element Method?

Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz, Carola-Bibiane Schönlieb

CoRR, 2023

2022

Losing momentum in continuous-time stochastic optimisation.

Kexin Jin, Jonas Latz, Chenguang Liu, Alessandro Scagliotti

CoRR, 2022

Gradient flows and randomised thresholding: sparse inversion and classification.

Jonas Latz

CoRR, 2022

2021

Error Analysis for Probabilities of Rare Events with Approximate Models.

Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann

SIAM J. Numer. Anal., 2021

Generalized parallel tempering on Bayesian inverse problems.

Jonas Latz, Juan P. Madrigal-Cianci, Fabio Nobile, Raúl Tempone

Stat. Comput., 2021

Analysis of stochastic gradient descent in continuous time.

Jonas Latz

Stat. Comput., 2021

A Continuous-time Stochastic Gradient Descent Method for Continuous Data.

Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb

CoRR, 2021

2020

Multilevel Sequential Importance Sampling for Rare Event Estimation.

Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann

SIAM J. Sci. Comput., 2020

Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems.

Ionut-Gabriel Farcas, Jonas Latz, Elisabeth Ullmann, Tobias Neckel, Hans-Joachim Bungartz

SIAM J. Sci. Comput., 2020

On the Well-posedness of Bayesian Inverse Problems.

Jonas Latz

SIAM/ASA J. Uncertain. Quantification, 2020

Classification and image processing with a semi-discrete scheme for fidelity forced Allen-Cahn on graphs.

Jeremy Budd, Yves van Gennip, Jonas Latz

CoRR, 2020

Certified and fast computations with shallow covariance kernels.

Daniel Kressner, Jonas Latz, Stefano Massei, Elisabeth Ullmann

CoRR, 2020

2019

Exploring and exploiting hierarchies in Bayesian inverse problems (Hierarchische Methoden und Modelle in der Bayes'schen Inversion)

Jonas Latz

PhD thesis, 2019

Bayesian Parameter Identification in Cahn-Hilliard Models for Biological Growth.

Christian Kahle, Kei Fong Lam, Jonas Latz, Elisabeth Ullmann

SIAM/ASA J. Uncertain. Quantification, 2019

2018

Multilevel Sequential² Monte Carlo for Bayesian inverse problems.

Jonas Latz, Iason Papaioannou, Elisabeth Ullmann

J. Comput. Phys., 2018

Fast sampling of parameterised Gaussian random fields.

Jonas Latz, Marvin Eisenberger, Elisabeth Ullmann

CoRR, 2018