Dr Linus Wunderlich
Lecturer in Financial Mathematics
School of Mathematical Sciences
Queen Mary University of London
Queen Mary University of London
Research
Mathematical foundation of AI, Deep Neural Networks, Option Pricing, Counterparty Credit Risk, Chebyshev Interpolation, Deep parametric PDE method
Interests
Linus' research combines machine learning with numerical techniques in mathematical finance. His work includes solving high-dimensional PDEs with neural networks and accelerated risk computations using Chebyshev interpolations. His research interest extends to the mathematical understanding of artificial intelligence and their wider applications.Publications
Publications of specific relevance to the Centre for Probability, Statistics and Data Science2023
Glau K and Wunderlich L (2023). Neural network expression rates and applications of the deep parametric PDE method in counterparty credit risk. Annals of Operations Research, Springer, 1-27. 13-04-2023
2022
Wunderlich L and Glau K (2022). The Deep Parametric PDE Method and Applications to Option Pricing. Applied Mathematics and Computation, Elsevier 02-07-2022
2021
Schlembach C, Schmidt SL, Schreyer D and Wunderlich L (2021). Forecasting the Olympic medal distribution – A socioeconomic machine learning model. Technological Forecasting and Social Change, Elsevier, 121314-121314. 12-11-2021
2018
Bayat HR, Krämer J, Wunderlich L, Wulfinghoff S, Reese S, Wohlmuth B and Wieners C (2018). Numerical evaluation of discontinuous and nonconforming finite element methods in nonlinear solid mechanics. Computational Mechanics 23-03-2018
2015
Steinbach O, Wohlmuth B and Wunderlich L (2015). Trace and flux a priori error estimates in finite-element approximations of Signorni-type problems. IMA Journal of Numerical Analysis, Oxford University Press (OUP) vol. 36 (3), 1072-1095. 24-07-2015
Brivadis E, Buffa A, Wohlmuth B and Wunderlich L (2015). Isogeometric mortar methods. Computer Methods in Applied Mechanics and Engineering, Elsevier vol. 284, 292-319. 01-02-2015
Grants
Grants of specific relevance to the Centre for Probability, Statistics and Data ScienceEfficient interpolation of the implied volatilityKathrin Glau and Linus Wunderlich
£10,800 Numerical Algorithms Group Ltd (01-11-2018 - 31-01-2019)