Jonas Latz

Orcid: 0000-0002-4600-0247

According to our database1, Jonas Latz authored at least 27 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Correction to: analysis of stochastic gradient descent in continuous time.
Stat. Comput., August, 2024

Adaptive Stepsize Algorithms for Langevin Dynamics.
SIAM J. Sci. Comput., 2024

Nested Sampling for Uncertainty Quantification and Rare Event Estimation.
SIAM J. Sci. Comput., 2024

The random timestep Euler method and its continuous dynamics.
CoRR, 2024

How to beat a Bayesian adversary.
CoRR, 2024

Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds.
CoRR, 2024

A Learnable Prior Improves Inverse Tumor Growth Modeling.
CoRR, 2024

Subsampling Error in Stochastic Gradient Langevin Diffusions.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Bayesian Inverse Problems Are Usually Well-Posed.
SIAM Rev., August, 2023

Joint Reconstruction-Segmentation on Graphs.
SIAM J. Imaging Sci., June, 2023

A Continuous-time Stochastic Gradient Descent Method for Continuous Data.
J. Mach. Learn. Res., 2023

Subsampling in ensemble Kalman inversion.
CoRR, 2023

Can Physics-Informed Neural Networks beat the Finite Element Method?
CoRR, 2023

2022
Losing momentum in continuous-time stochastic optimisation.
CoRR, 2022

Gradient flows and randomised thresholding: sparse inversion and classification.
CoRR, 2022

2021
Error Analysis for Probabilities of Rare Events with Approximate Models.
SIAM J. Numer. Anal., 2021

Generalized parallel tempering on Bayesian inverse problems.
Stat. Comput., 2021

Analysis of stochastic gradient descent in continuous time.
Stat. Comput., 2021

2020
Multilevel Sequential Importance Sampling for Rare Event Estimation.
SIAM J. Sci. Comput., 2020

Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems.
SIAM J. Sci. Comput., 2020

On the Well-posedness of Bayesian Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2020

Classification and image processing with a semi-discrete scheme for fidelity forced Allen-Cahn on graphs.
CoRR, 2020

Certified and fast computations with shallow covariance kernels.
CoRR, 2020

2019
Exploring and exploiting hierarchies in Bayesian inverse problems (Hierarchische Methoden und Modelle in der Bayes'schen Inversion)
PhD thesis, 2019

Bayesian Parameter Identification in Cahn-Hilliard Models for Biological Growth.
SIAM/ASA J. Uncertain. Quantification, 2019

2018
Multilevel Sequential<sup>2</sup> Monte Carlo for Bayesian inverse problems.
J. Comput. Phys., 2018

Fast sampling of parameterised Gaussian random fields.
CoRR, 2018


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