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 :	jlatzma.tum.de

Research

Uncertainty Quantification & Bayesian Inverse Problems: Monte Carlo, Markov Chain Monte Carlo, Sequential Monte Carlo, Ensemble Kalman Filter, Multilevel Methods, Random fields
Bayesian Statistics: Bayesian Model Selection, Hyperpriors, Bayes Linear Statistics
Numerical Analysis: Reduced Basis Methods
Applications: Engineering (ERA) and Biology
Further interests: Machine Learning, Measure Theory, Approximation of Probability Distributions, Boolean Algebra, Interpretation and Foundations of Probability and Statistics, Matroids

Jonas Latz, Iason Papaioannou, Elisabeth Ullmann (2017): Multilevel Sequential² Monte Carlo for Bayesian Inverse Problems, submitted to J. Comp. Phys., arXiv e-print 1709.09763

(April 16th-19th 2018) Minisymposium Multilevel and multifidelity Bayesian methods for inverse problems and beyond, SIAM UQ 18 , Garden Grove, CA, USA.
(September 6th-8th 2017) FrontUQ in Engineering, Munich, Germany.
(June 15th-17th 2017) UNCECOMP 2017 , Rhodes, Greece.
(March 24th 2017) Group Seminar, Hybrid Materials Interfaces Group, Universität Bremen, Germany.

(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,
(Term 1/2 2015/16) Undergraduate Supervisor (Mathematics Institute, University of Warwick),
(Summer term 2015) Tutorials in Elemente der Analysis 2 (Fachbereich IV, Universität Trier),
(Winter term 2014/15) Tutorials in Elemente der Analysis 1 and Tutorials in Mikroökonomik (Fachbereich IV, Universität Trier),
(Winter term 2013/14) Tutorials in Mikroökonomik (Fachbereich IV, Universität Trier).

(ongoing) Marvin Eisenberger (M.Sc. student, working title: Efficient parameterised solving of KL Eigenproblems)

(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

Jonas Latz (2016): Bayes Linear Methods for Inverse Problems, Master's Thesis, University of Warwick. (*.pdf | *.bib)