Personal page of Dr. Stefan Richter

Member of Statistics of stochastic processes
Position	PostDoc
Office	INF 205, 4/223
E-Mail	stefan.richter[at]iwr.uni-heidelberg.de
Telephone	+49 6221 54 14181

Research Interests

Statistical Learning
Highdimensional Time Series Data
Technical finance analysis (in collaboration with Dragoljub Katic)

Publications and Preprints

Books and lecture notes:

(Sep/2019) Stefan Richter: Statistisches und maschinelles Lernen, Springer Verlag Link
(Jul/2021) Stefan Richter: Tutorial: Statistical analysis of machine learning algorithms (143 pages)

Papers und Preprints:

(2024) Jiaqi Li, Zhipeng Lou, Stefan Richter, Wei Biao Wu: The stochastic gradient descent from a nonlinear time series perspective - Material
(2023) Stefan Richter, Weining Wang, Wei Biao Wu: Testing for parameter change epochs in GARCH time series, The Econometrics Journal Link
(2022) Nathawut Phandoidaen, Stefan Richter: Empirical process theory for nonsmooth functions under functional dependence, Electronic Journal of Statistics, Link
(2022) Nathawut Phandoidaen, Stefan Richter: Empirical process theory for locally stationary processes, Bernoulli, Link
(2022) Rainer Dahlhaus, Stefan Richter: Adaptation for nonparametric estimators of locally stationary processes, Econometric Theory, 1-31. Link
(2022) Sayar Karmakar, Stefan Richter, Wei Biao Wu: Simultaneous inference for time-varying models, Journal of Econometrics, 227(2), 408-428. Link
(2020) Stefan Richter, Ekaterina Smetanina: Forecast Evaluation and Selection in Unstable Environments - under revision in the Journal of EconometricsMaterial
(2020) Moritz Haas, Stefan Richter: Statistical analysis of Wasserstein GANs with applications to time series forecasting - Material
(2020) Nathawut Phandoidaen, Stefan Richter: Forecasting time series with encoder-decoder neural networks, arXiv, to appear. arXiv:2009.08848
(2019) Stefan Richter, Rainer Dahlhaus: Cross Validation for locally stationary processes, Annals of Statistics.Link
(2019) Rainer Dahlhaus, Stefan Richter, Wei Biao Wu: Towards a general theory for locally stationary processes, Bernoulli. Link

Lecturer for:

Semester	Name
Winter term 2023/2024	Lecture Statistical analysis of machine learning algorithms
Summer term 2023	Lecture Probability Theory 2
Winter term 2022/2023	Lecture Discrete and continuous time financial mathematics
Summer term 2021	Seminar Probability theory and statistics for stationary processes
Winter term 2020/2021	Lecture Statistical analysis of machine learning algorithms
Winter term 2020/2021	Seminar Regression analysis and highdimensional data
Summer term 2020	Lecture Probability theory 1
Winter term 2019/2020	Seminar Mathematical Statistics in Machine Learning

Teaching assistant for:

Semester	Name
Winter term 2023/2024	Lecture Statistical analysis of machine learning algorithms
Summer term 2021	Lecture Probability Theory 2
Summer term 2021	Seminar Probability theory and statistics for stationary processes
Winter term 2020/2021	Lecture Statistical analysis of machine learning algorithms
Winter term 2020/2021	Seminar Regression analysis and highdimensional data
Summer term 2020	Lecture Probability theory 1
Summer term 2019	Lecture Linear Algebra 2
Winter term 2018/2019	Lecture Linear Algebra 1
Summer term 2017	Seminar Dynamical Models for Networks
Summer term 2017	Lecture Probability Theory 2
Winter term 2016/2017	Lecture Statistics 1
Summer term 2016	Lecture Wahrscheinlichkeitstheorie 1