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)^[6-7], (Probability Theory and Statistics)^[1-2,4-5] that can be used to blend mathematical models with observational data.

Publications

Preprints

• [7] Felipe Uribe, Iason Papaioannou, Jonas Latz, Wolfgang Betz, Elisabeth Ullmann, Daniel Straub (2019)
  Bayesian inference with subset simulation in spaces of varying dimension
  Under review. (Abstract, *.bib, Preprint)
• [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)
• (2019) 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 , Google Scholar 
• 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)