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ORCIDJonas Latz
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2020 – today
- 2024
[j13]Jonas Latz
:
Correction to: analysis of stochastic gradient descent in continuous time. Stat. Comput. 34(4): 146 (2024)- [j12]Jonas Latz, Doris Schneider, Philipp Wacker:
Nested Sampling for Uncertainty Quantification and Rare Event Estimation. SIAM J. Sci. Comput. 46(5): 3305- (2024) - [c1]Kexin Jin, Chenguang Liu, Jonas Latz:
Subsampling Error in Stochastic Gradient Langevin Diffusions. AISTATS 2024: 1414-1422 - [i20]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:
A Learnable Prior Improves Inverse Tumor Growth Modeling. CoRR abs/2403.04500 (2024) - [i19]Alix Leroy, Benedict J. Leimkühler, Jonas Latz, Desmond J. Higham:
Adaptive stepsize algorithms for Langevin dynamics. CoRR abs/2403.11993 (2024) - [i18]Liam Llamazares-Elias, Samir Llamazares-Elías, Jonas Latz, Stefan Klus:
Data-driven approximation of Koopman operators and generators: Convergence rates and error bounds. CoRR abs/2405.00539 (2024) - [i17]Zihan Ding, Kexin Jin, Jonas Latz, Chenguang Liu:
How to beat a Bayesian adversary. CoRR abs/2407.08678 (2024) - [i16]Jonas Latz:
The random timestep Euler method and its continuous dynamics. CoRR abs/2408.01409 (2024) - 2023
- [j11]Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb:
A Continuous-time Stochastic Gradient Descent Method for Continuous Data. J. Mach. Learn. Res. 24: 274:1-274:48 (2023) - [j10]Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb:
Joint Reconstruction-Segmentation on Graphs. SIAM J. Imaging Sci. 16(2): 911-947 (2023) - [j9]Jonas Latz:
Bayesian Inverse Problems Are Usually Well-Posed. SIAM Rev. 65(3): 831-865 (2023) - [i15]Tamara G. Grossmann, Urszula Julia Komorowska, Jonas Latz, Carola-Bibiane Schönlieb:
Can Physics-Informed Neural Networks beat the Finite Element Method? CoRR abs/2302.04107 (2023) - [i14]Matei Hanu, Jonas Latz, Claudia Schillings:
Subsampling in ensemble Kalman inversion. CoRR abs/2302.11323 (2023) - [i13]Kexin Jin, Chenguang Liu, Jonas Latz:
Subsampling Error in Stochastic Gradient Langevin Diffusions. CoRR abs/2305.13882 (2023) - 2022
- [i12]Jonas Latz:
Gradient flows and randomised thresholding: sparse inversion and classification. CoRR abs/2203.11555 (2022) - [i11]Jeremy Budd, Yves van Gennip, Jonas Latz, Simone Parisotto, Carola-Bibiane Schönlieb:
Joint reconstruction-segmentation on graphs. CoRR abs/2208.05834 (2022) - [i10]Kexin Jin, Jonas Latz, Chenguang Liu, Alessandro Scagliotti:
Losing momentum in continuous-time stochastic optimisation. CoRR abs/2209.03705 (2022) - 2021
- [j8]Jonas Latz:
Analysis of stochastic gradient descent in continuous time. Stat. Comput. 31(4): 39 (2021) - [j7]Jonas Latz, Juan P. Madrigal-Cianci, Fabio Nobile, Raúl Tempone:
Generalized parallel tempering on Bayesian inverse problems. Stat. Comput. 31(5): 67 (2021) - [j6]Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann:
Error Analysis for Probabilities of Rare Events with Approximate Models. SIAM J. Numer. Anal. 59(4): 1948-1975 (2021) - [i9]Kexin Jin, Jonas Latz, Chenguang Liu, Carola-Bibiane Schönlieb:
A Continuous-time Stochastic Gradient Descent Method for Continuous Data. CoRR abs/2112.03754 (2021) - 2020
- [j5]Jonas Latz:
On the Well-posedness of Bayesian Inverse Problems. SIAM/ASA J. Uncertain. Quantification 8(1): 451-482 (2020) - [j4]Ionut-Gabriel Farcas, Jonas Latz, Elisabeth Ullmann, Tobias Neckel, Hans-Joachim Bungartz:
Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems. SIAM J. Sci. Comput. 42(1): A424-A451 (2020) - [j3]Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann:
Multilevel Sequential Importance Sampling for Rare Event Estimation. SIAM J. Sci. Comput. 42(4): A2062-A2087 (2020) - [i8]Daniel Kressner, Jonas Latz, Stefano Massei, Elisabeth Ullmann:
Certified and fast computations with shallow covariance kernels. CoRR abs/2001.09187 (2020) - [i7]Jonas Latz, Juan P. Madrigal-Cianci, Fabio Nobile, Raúl Tempone:
Generalized Parallel Tempering on Bayesian Inverse Problems. CoRR abs/2003.03341 (2020) - [i6]Jonas Latz:
Analysis of Stochastic Gradient Descent in Continuous Time. CoRR abs/2004.07177 (2020) - [i5]Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann:
Error analysis for probabilities of rare events with approximate models. CoRR abs/2008.06368 (2020) - [i4]Jeremy Budd, Yves van Gennip, Jonas Latz:
Classification and image processing with a semi-discrete scheme for fidelity forced Allen-Cahn on graphs. CoRR abs/2010.14556 (2020)
2010 – 2019
- 2019
- [b1]Jonas Latz:
Exploring and exploiting hierarchies in Bayesian inverse problems (Hierarchische Methoden und Modelle in der Bayes'schen Inversion). Technical University of Munich, Germany, 2019 - [j2]Christian Kahle, Kei Fong Lam, Jonas Latz, Elisabeth Ullmann:
Bayesian Parameter Identification in Cahn-Hilliard Models for Biological Growth. SIAM/ASA J. Uncertain. Quantification 7(2): 526-552 (2019) - [i3]Ionut-Gabriel Farcas, Jonas Latz, Elisabeth Ullmann, Tobias Neckel, Hans-Joachim Bungartz:
Multilevel adaptive sparse Leja approximations for Bayesian inverse problems. CoRR abs/1904.12204 (2019) - [i2]Fabian Wagner, Jonas Latz, Iason Papaioannou, Elisabeth Ullmann:
Multilevel Sequential Importance Sampling for Rare Event Estimation. CoRR abs/1909.07680 (2019) - 2018
- [j1]Jonas Latz, Iason Papaioannou, Elisabeth Ullmann:
Multilevel Sequential2 Monte Carlo for Bayesian inverse problems. J. Comput. Phys. 368: 154-178 (2018) - [i1]Jonas Latz, Marvin Eisenberger, Elisabeth Ullmann:
Fast sampling of parameterised Gaussian random fields. CoRR abs/1804.11157 (2018)
Coauthor Index
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last updated on 2024-10-22 21:13 CEST by the dblp team
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