Jonas Latz, M.Sc.

Name :	Jonas Latz
Address :	M2 - Lehrstuhl für Numerische Mathematik
	Boltzmannstraße 3
	85748 Garching b.M.
Office :	03.10.055
Phone :	+49 89 289 18404
E-mail :	jonas.latztum.de (Send me an encrypted email)

Research

Interests

Methods in (Numerical Analysis)^[3], (Computational Science)^[6], (Probability Theory and Statistics)^[1-2,4-5] that can be used to blend mathematical models with observational data.

Publications

Preprints

[6] Ionuţ-Gabriel Farcaş, Jonas Latz, Elisabeth Ullmann, Tobias Neckel, Hans-Joachim Bungartz (2019)
Multilevel Adaptive Sparse Leja Approximations for Bayesian Inverse Problems
Under review. (Abstract, *.bib, arXiv )
[5] Jonas Latz (2019)
On the well-posedness of Bayesian inverse problems
Under review. (Abstract, *.bib, arXiv )

Refereed journal publications

[4] Christian Kahle, Kei Fong Lam, Jonas Latz, Elisabeth Ullmann (2019)
Bayesian parameter identification in Cahn-Hilliard models for biological growth
SIAM/ASA J. Uncertain. Quantif. 7(2), p. 526-552, DOI . (Abstract, *.bib, arXiv )
[3] Jonas Latz, Marvin Eisenberger, Elisabeth Ullmann (2019)
Fast Sampling of parameterised Gaussian random fields
Comput. Methods in Appl. Mech. Engrg. 348, p. 978-1012, DOI . (Abstract, *.bib, arXiv )
[2] Jonas Latz, Iason Papaioannou, Elisabeth Ullmann (2018)
Multilevel Sequential² Monte Carlo for Bayesian Inverse Problems
J. Comput. Phys. 368, p. 154-178, DOI . (Abstract, *.bib, arXiv )

Refereed book chapters

[1] Matthieu Bulté, Jonas Latz, Elisabeth Ullmann (2018)
A practical example for the non-linear Bayesian filtering of model parameters
Accepted. (github , Abstract, *.bib, arXiv )

Talks

2019

(June 30th- July 5th 2019) 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2019) , Max Planck Institute for Plasma Physics, Garching, Germany.
(March 10th-16th 2019) Oberwolfach Workshop 1911 "Uncertainty Quantification" , Mathematisches Forschungsinstitut Oberwolfach, Germany.
(February 25th - March 1st 2019) SIAM Conference on Computational Science and Engineering (CSE19) , Spokane, WA, USA. (Video )
(February 21st 2019) Seminar/Group Meeting "RTG Mathematical Modelling and Simulation" , Courant Institute of Mathematical Sciences, New York, NY, USA. (Slides)
(January 23rd 2019) Warwick SIAM Student Chapter's conference on "High Dimensional Inference and Monte Carlo Techniques" , University of Warwick, Coventry, United Kingdom.

2018

(October 22nd 2018) Seminar ANCHP + CSQI, École Polytechnique Fédérale de Lausanne, Switzerland.
(September 20th 2018) Seminar CSQI, École Polytechnique Fédérale de Lausanne, Switzerland.
(July 1st-6th 2018) 13th International Conference in Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing (MCQMC 2018) , Rennes, France.
(April 16th-19th 2018) SIAM Conference on Uncertainty Quantification 2018 (UQ18) , Garden Grove, CA, USA.
(March 19th-23rd 2018) GAMM Annual Meeting 2018 , Munich, Germany.
(February 20th 2018) Seminar , Isaac Newton Institute, Cambridge, United Kingdom.

2017

(February 5th-9th 2018) Surrogate models for UQ in complex systems , Isaac Newton Institute, Cambridge, United Kingdom. (Poster)
(November 22nd 2017) Seminar Stochastics, Statistics and Numerical Analysis, Universität Mannheim, Germany. (Slides)
(September 6th-8th 2017) FrontUQ in Engineering, Munich, Germany.
(June 15th-17th 2017) 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017) , Rhodes, Greece.
(March 24th 2017) Group Seminar, Hybrid Materials Interfaces Group, Universität Bremen, Germany.

Stays

(February 20th-22nd 2019) Courant Institute of Mathematical Sciences, New York, NY, USA. (with Benjamin Peherstorfer)
(January 24th-25th 2019) Chair of Applied Mathematics, University of Manchester, UK. (with Kody J.H. Law)
(September - November 2018) Chair of Scientific Computing and Uncertainty Quantification, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. (with Fabio Nobile)
(February 5th-23rd 2018) Isaac Newton Institute, University of Cambridge, UK.
(November 20th-22nd 2017) Chair of Mathematical Optimization, Universität Mannheim, Germany. (with Claudia Schillings)

Teaching

Lectures

(July 10th 2018) Guest lecture "Bayesian Inverse Problems" in Algorithms for Uncertainty Quantification, Chair for Scientific Computing, Computer Science, TUM.
(July 18th 2017) Guest lecture "Bayesian Inverse Problems" in Algorithms for Uncertainty Quantification, Chair for Scientific Computing, Computer Science, TUM.

Tutorials

Technische Universität München, Zentrum Mathematik

(Winter term 2018/19) Supervision in Hauptseminar: Data assimilation,
(Summer term 2018) Tutorials in Numerical Methods for Uncertainty Quantification,
(Winter term 2017/18) Tutorials in Einführung in die Numerische Lineare Algebra,
(Summer term 2017) Tutorials in Numerical Methods for Uncertainty Quantification and Supervision in Hauptseminar: Uncertainty Quantification with Efficient Monte Carlo Methods,
(Winter term 2016/17) Tutorials in Maß- und Integrationstheorie,

University of Warwick, Mathematics Institute, UK

(Term 1/2 2015/16) Undergraduate Supervisor,

Universität Trier, Fachbereich IV

(Summer term 2015) Tutorials in Elemente der Analysis 2,
(Winter term 2014/15) Tutorials in Elemente der Analysis 1 and Tutorials in Mikroökonomik,
(Winter term 2013/14) Tutorials in Mikroökonomik.

Supervised students

Bachelor's theses

(ongoing) Samuel Amar (working title: Adaptive Metropolis for Bayesian inference in crystallography)
(ongoing) Sarah Kreuzer (title: Efficient implementation of the Ising-model and image denoising)
(2018) Matthieu Bulte (title: Sequential Monte Carlo for time-dependent Bayesian Inverse Problems)

Master's theses

(2018) Sabrina Balzer (title: Gaussian process surrogates for Bayesian parameter identification in computational oncology; with Christian Kahle and Elisabeth Ullmann)
(2018) Fabian Wagner (title: Particle Methods for Deep Learning)
(2017) Marvin Eisenberger (title: Parameterized solution of Karhunen-Loève Eigenproblems with Reduced Basis Methods in Uncertainty Quantification, now: TUM Dep. Informatics)

Education

Degree programmes

(ongoing) Doctoral Studies in Mathematics, Technische Universität München, Germany
(2015-2016) Master of Science in Scientific Computing (with Distinction), University of Warwick, UK
(2014-2016) Master of Science in Applied Mathematics and Economics, Universität Trier, Germany
(2012-2014) Bachelor of Science in Business Mathematics, Universität Trier

Theses

Jonas Latz (2016)
Bayes Linear Methods for Inverse Problems
Master's Thesis, University of Warwick. (*.pdf | *.bib)
Jonas Latz (2014)
Äußere Hausdorff Maße: Anwendungen und Eigenschaften
Bachelor's Thesis, Universität Trier.

Useful(?!) Links

Reading Group Uncertainty Quantification
Project 10.02/BAYES@International Graduate School of Science and Engineering at TUM.
Networks: GitHub\latz-io , orcid.org , researchgate
Lunch menus@Garching: FMI Cafeteria, IPP Canteen , Mensa
Science Communication:
- Uncertaintea Quantification (Youtube) , Science Slam, Hamburg, 2017 (in German)
- Latz, Ullmann: Bayes'sche Inversion am Beispiel des Fadenpendels, in Quartl 84, Garching, 2017 (in German)
- Latz, Ullmann: Wie lernen Computer die Erdbeschleunigung?, in TUM Campus Magazin, 01/2018 (in German)