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Contact

nadja.klein at
statistik.tu-dortmund.de
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N.N.
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News

  • We welcome Maarten Jung as research assistant and Annalena Weißert as student assistant to our group. (01.04.2023)
  • The paper "Approximate Bayesian computation for parameter identification in computational mechanics" by Matthias G. R. Faes, Nadja Klein, Markus Pauly, Marcos A. Valdebenito and Mauricio A. Misraji was accepted to the 14th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP14). (28.03.2023)
  • We have job openings for a PhD position and PostDoc position in our group! (27.02.2023)
  • The paper "Boosting Multivariate Structured Additive Distributional Regression Models" by Annika Strömer, Nadja Klein, Christian Staerk, Hannah Klinkhammer and Andreas Mayr was accepted for publication in Statistics in Medicine. The arXiv preprint can be found here. (24.02.2023)
  • Clara Hoffmann is going to present at the PyCon DE & PyData Berlin 2023 (17. April - 19. April 2023) on debugging custom PyTorch models in a structured manner. More details regarding her talk can be found here. (21.02.2023)
  • The paper "Bayesian Conditional Transformation Models" by Manuel Carlan, Thomas Kneib and Nadja Klein was accepted for publication in the Journal of the American Statistical Association. The arXiv preprint can be found here. (21.02.2023)
  • The paper "Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices" by Nadja Klein, Michael Stanley Smith and David J. Nott (Journal of Applied Econometrics) can be found here. (21.02.2023)
  • The paper "Modeling Intra-Annual Tree Stem Growth with a Distributional Regression Approach for Gaussian Process Responses" by Hannes Riebl, Nadja Klein and Thomas Kneib was accepted at Journal of the Royal Statistical Society, Series C (Applied Statistics). (21.01.2023)
  • A new working paper "Scalable Estimation for Structured Additive Distributional Regression" by Nikolaus Umlauf, Johannes Seiler, Matthias Wetscher, Thorsten Simon, Stefan Lang and Nadja Klein can be found here. (13.01.2023)
  • The paper "Semi-Structured Distributional Regression" by David Ruegamer, Chris Kolb and Nadja Klein was accepted at The American Statistician. (01.01.2023)
  • We welcome Ivan Ustyuzhaninov as postdoctoral researcher, Clara Hoffmann as PhD student and Tim-Moritz Bündert as research assistant to our group. (01.01.2023)
  • We will move from Humboldt-Universität zu Berlin to TU Dortmund in April 2023! (01.01.2023)
  • New working paper "Accounting for Time Dependency in Meta-Analyses of Concordance Probability Estimates" by Matthias Schmid, Tim Friede, Nadja Klein and Leonie Weinhold can be found here. (03.12.2022)
  • New working paper "Anisotropic multidimensional smoothing using Bayesian tensor product P-splines" by Paul Bach and Nadja Klein can be found here. (29.11.2022)
  • New working paper "Informed Priors for Knowledge Integration in Trajectory Prediction" by Christian Schlauch, Nadja Klein and Christian Wirth can be found here. (01.11.2022)
  • New working paper "Distributional Adaptive Soft Regression Trees" by Nikolaus Umlauf and Nadja Klein can be found here. (19.10.2022)

Team

Prof. Dr. Nadja Klein Nadja Klein Group Lead ___________

    Curriculum Vitae

    Short Vita

    from Apr. 2023 Full research professorship (W3) for Uncertainty Quantification and Statistical Learning at the Department of Statistics (TU Dortmund) and Research Center Trustworthy Data Science and Security
    Oct. 2021 - Apr. 2023 Full professorship (W3) for Statistics and Data Science, Humboldt-Universität zu Berlin
    Nov. 2019 - Apr. 2023 Emmy Noether Research Group Leader in Statistics & Data Science, Humboldt-Universität zu Berlin
    Oct. 2018 - Sep. 2021 (Non-tenured) Assistant professorship (W1) for Applied Statistics, Humboldt-Universität zu Berlin
    Apr. 2018 - Oct. 2018 (Non-tenured) Assistant professorship (W1) for Statistics, Universität zu Köln
    Jul. 2016 - Feb. 2018 Postdoctoral Feodor Lynen Fellow of the Alexander von Humboldt Foundation, Melbourne Business School, University of Melbourne, Host: Prof. Dr. Michael Smith
    Oct. 2015 - Sept. 2016 Postdoctoral Fellow of the Fonds Wetenschappelijk Onderzoek - Vlaanderen, supervisor: Prof. Dr. Gerda Claeskens (unpaid leave)
    Jan. 2015 - Mar. 2018 Postdoctoral researcher, Georg-August-Universität Göttingen
    Jan. 2015 Dr. rer. nat. in Mathematics, Georg-August-Universität Göttingen Thesis title: Bayesian Structured Additive Distributional Regression, summa cum laude
    Supervisor: Prof. Dr. Thomas Kneib, defence: 03/12/2014
    Mar. 2012 - Dec. 2014 Doctoral studies in Mathematics
    PhD school Georg-August University School of Science (GAUSS)
    Georg-August-Universität Göttingen
    Jan. 2012 Diploma in Mathematics with a minor in Physics, Universität Hamburg
    Thesis title: Statistische Lebenszeitanalyse von Flugzeuggeräten, sehr gut
    Supervisor: Prof. Dr. Holger Drees, diploma examination: 26/01/2012
    Apr. 2007 - Feb. 2012 Studies in Mathematics with a minor in Physics, Johannes-Gutenberg-Universität Mainz and Universität Hamburg

    Supervision

    Membership in Habilitation Committees

    2022 Dr. Moritz Berger: Fortgeschrittene Methoden zur Modellierung von diskreten Ereigniszeiten (Universität Bonn)

    Postdocs

    from 2023 Ivan Ustyuzhaninov
    since Oct. 2022 PhD Victor Medina-Olivares
    2021 - 2022 PhD Stephen Johnson
    2021 - 2022 Dr. Tim Kutzker

    PhD Theses (1. Supervisor)

    from Feb. 2023 PhD thesis of Clara Hoffmann: Calibrated Deep Response Distributions for Understanding Disease Progression (Technische Universität Dortmund)
    since Sep. 2022 PhD thesis of Ekin Celikkan: Bayesian Machine Learning with Uncertainty Quantification for Detecting Weeds in Crop Lands from Low Altitude Remote Sensing (Humboldt-Universität zu Berlin & HEIBRiDS PhD Program)
    since Jun. 2022 PhD thesis of Christian Schlauch: Continual Bayesian Deep learning with knowledge integration (Humboldt-Universität zu Berlin & Continental AG/KI Wissen)
    since Jan. 2020 PhD thesis of Annika Strömer: Boosting copulas Boosting copulas (Universität Bonn, joint supervision with Prof. Mayr)
    since Dec. 2019 PhD thesis of Paul Bach: Properties of non-local priors for distributional regression (Humboldt-Universität zu Berlin)
    since Oct. 2019 PhD thesis of Lucas Kock: Deep Gaussian mixture models (Humboldt-Universität zu Berlin)
    2020 - 2022 PhD thesis of Nicolai Hans: Boosting copulas in medicine (Humboldt-Universität zu Berlin)
    2017 - 2022 PhD thesis of Hannes Riebl: Spatio-temporal distributional regression modelling (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib)
    2017 - 2020 PhD thesis of Isa Marques: Recent advances in continuous space spatial statistics: From Non-stationarity to spatial confounding (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib)
    2016 - 2020 PhD thesis of Manuel Carlan: Bayesian distributional regression: From effect selection priors in generalized additive models for location, scale and shape to Bayesian conditional transformation models (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib)

    Awards and Prizes

    2022 Nomination to AcademiaNet (Swiss National Science Foundation; the expert database for outstanding female academics), Profile
    2022 Gustav-Adolf-Lienert-Award of the International Biometric Sociecty, German Region (IBS-DR) for the Biometrics paper Bayesian Variable Selection for Non-Gaussian Responses: A Marginally Calibrated Copula Approach
    2022 Leadership Programme for Female Professors 2022
    2022 Awarded membership in Die Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina
    2018 ISBA Young Researcher Travel Support
    since 2016 Awarded membership in the Humboldt network (by the Alexander von Humboldt Foundation)
    2016 Feodor Lynen Fellowship for Postdoctoral Researchers of the Alexander von Humboldt Foundation
    2016 NSF-ISBA Junior Travel Support Grant of the US National Science Foundation
    2015 Wolfgang-Wetzel-Price 2015 of the German Statistical Society for the JASA paper Bayesian Generalized Additive Models for Location, Scale and Shape for Zero-Inflated and Overdispersed Count Data
    2014 Award of the Georg-August-Universität Göttingen for outstanding dissertation Bayesian Structured Additive Distributional Regression
    2014 Award of the Universitätsbund Göttingen for the dissertation Bayesian Structured Additive Distributional Regression
    Oct. 2013 - Oct. 2014 Awarded Membership in the Dorothea Schlözer Mentoring Programme, Georg-August-Universität Göttingen

    Memberships

    since Jun. 2022 Partner Membership at the Institute of Informatics (Humboldt-Universität zu Berlin)
    since Jan. 2022 Partner Membership at the Institute of Mathematics (Humboldt-Universität zu Berlin)
    since Oct. 2021 Member of International Biometric Society (IBS)
    since May 2021 Member of International Society of Bayesian Analysis (ISBA)
    since Jul. 2020 Member of Die Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina
    since Aug. 2019 Member of the Math+ Research Center and Berlin Mathematical School (BMS), TU Berlin, FU Berlin and HU Berlin
    since May 2019 Member of the Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), HU Berlin
    since Jan. 2019 Member of the Berlin Doctoral Program in Economics and Management Science (BDPEMS)
    since Dec. 2018 Member of Biostatnet
    since Oct. 2018 Member of the Joint Commission of the Master in Statistics, Berlin
    since Apr. 2018 Associate member of the DFG Research Training Group 2300 Enrichment of European beech forests with conifers: impacts of functional traits on ecosystem functioning
    since Nov. 2018 Member of Berlin Economics Research Associates (BERA)
    since Apr. 2018 Member of The German Statistical Society (DStatG)
    since Jan. 2018 American Statistical Association (ASA) Early Career Member
    since Aug. 2017 Member of The German Association of University Professors and Lecturers (DHV)
    since Jan. 2017 Member of the Bayesian Analysis and Modeling Research Group, University of Melbourne
    Mar. 2015 - Mar. 2018 Member of the Centre for Statistics, Georg-August-Universität Göttingen
    Oct. 2012 - Dec. 2014 Associate member of the DFG Research Training Group 1644 Scaling Problems in Statistics

    Professional Activities

    Journal Activity

    Editorial Advisory Board Member
    Guest Editor
    • Advances in Data Analysis and Classification, Special Issue: 'New methodologies interconnecting Statistical Learning, Data Science, and Artificial Intelligence for high-quality and timely statistics' (2023). Co-Editor together with Berthold Lausen
    • Biometrical Journal, Special Issue: Joint Modelling of Longitudinal and Time-To-Event Data and Beyond (2017), 59(6):1101-1403. Co-Editor together with Carmen Cadarso Suárez, Thomas Kneib, Geert Molenberghs and Dimitris Rizopoulos
    Associate Editor
    Referee

    Referee for Funding Agencies

    Service to University

    2022 Member of the Commission of the intermediate evaluation for the assistant professorship Industrial Economics of Prof Schweighöfer-Kodritsch
    since Nov. 2021 Examination Board of the Master in Statistics, Berlin
    since Oct. 2018 Member of the Joint Commission of the Master in Statistics, Berlin

    Further Activities and Volunteering

    since Dec. 2021 Liaison professor of the German Academic Scholarship Foundation
    since Nov. 2021 Speaker of the Research Group Artificial Intelligence, Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina
    2020 Course on “Good Supervision”

    Conferences

    Conference Activity

    Organizing Committee
    Organized Sessions
    Chaired Sessions

    Organization of Workshops and Retreats

    Recent Presentations and Posters

    • Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices at the Research Seminar of the Melbourne Business School (Melbourne, 31/08/2022)
    • Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices at the Research Seminar of the Macquarie Business School (University of Sydney, 18 - 20/08/2022)
    • Scalable, Calibrated (Deep) Probabilistic Learning at the Colloquium of the Department of Computer Science (Humboldt-Universität zu Berlin, 04/05/2022)
    • Bayesian Variable Selection for Non-Gaussian Responses - A Marginally Calibrated Copula Approach at the IBS Price Session (DAGStat 2022, UKE Hamburg, 28/03 - 01/04/2022)
    • Advances in Distributional Regression at the Bremer Kolloquium Epidemiologie - Public Health, BIPS Bremen (Competence Center for Clinical Trials, Universität Bremen, 22 - 23/09/2021)
    • Marginally Calibrated Deep Distributional Regression and Beyond at the Research Center Trustworthy Data Science and Security (Technische Universität Dortmund, 20 - 21/09/2021)
    • Marginally Calibrated Deep Distributional Regression (with an application to computationally challenging likelihood-free inference problems) at the Faculty of Statistics (Technische Universität Dortmund, 13/01/2021)
    • Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices at the School of Business and Economics (Humboldt-Universität zu Berlin, 20/11/2020)
    • Advances in Distributional Regression - Statistical Learning Approaches at the Faculty of Business and Economics (Georg-August-Universität Göttingen, 12/07/2020)
    • Bayesian Regression Copulas at the Mathematical Statistics Research Seminar (WIAS, Humboldt-Universität zu Berlin, 29/01/2020)

    Research Funding

    from 2023 PI of two sub-projects in DFG Research unit Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (sub-project P5, sub-project P6)
    since Aug. 2021 Experiment (Volkswagenstiftung)
    since Sep. 2020 Individual Research Grant Boosting Copulas (joint with Prof. A. Mayr, Universität Bonn, DFG)
    since Nov. 2019 Leader of the Emmy Noether Research Group Regression Models Beyond the Mean - A Bayesian Approach to Machine Learning (DFG)
    2020 - 2021 Berlin University Alliance Seed Fund (joint with Prof. D. Nott, National University of Singapore)
    Oct. 2019 - Sep. 2021 Klaus Tschira boost fund (German Scholars Organization e.V.)
    Aug. 2019 - Jul. 2020 Transferbonus with Newsenselab (Humboldt Innovations)
    Oct. 2017 - Apr. 2018 RTG 2300 Enrichment of European beech forests with conifers: impacts of functional traits on ecosystem functioning (speaker: Christian Ammer; own role: principle investigator until 04/2018)
    Jul. 2016 - Jun. 2018 Feodor Lynen fellowship of the Alexander von Humboldt Stiftung Multivariate Conditional Distributions (principle investigator: N. Klein)
Paul Bach Paul Bach PhD Student
Guillermo Briseno-Sanchez Guillermo Briseno-Sanchez PhD Student
Tim-Moritz Bündert Tim-Moritz Bündert Research Assistant
Ekin Celikkan Ekin Celikkan PhD Student
Clara Hoffmann Clara Hoffmann PhD Student
Maarten Jung Maarten Jung Research Assistant
Lucas Kock Lucas Kock PhD Student
Victor Medina-Olivares, PhD Victor Medina-Olivares Postdoctoral Researcher
Christian Schlauch Christian Schlauch PhD Student
Bettina Schmidt Bettina Schmidt PhD Student
Michael Stanley Smith Michael Stanley Smith Mercator Fellow
Ivan Ustyuzhaninov Ivan Ustyuzhaninov Postdoctoral Researcher
Annalena Weißert Annalena Weißert Student Assistant

Research

Research Interests

My research interests broadly lie at the intersection of machine learning and traditional statistical methods. This includes Bayesian Computational Methods, Bayesian Deep Learning, Machine Learning, Smoothing, Regularization and Shrinkage, Distributional Regression, Network Analysis as well as Spatial Statistics.

Ongoing Third-Party Research Projects

I am principal investigator in the following research projects.

Publications

See my Google Scholar entries for a complete list. Below you find some key publications and recent working papers.

Selected Publications

  • Multivariate Conditional Transformation Models pdf

    N. Klein, T. Hothorn, L. Barbanti and T. Kneib
    Scandinavian Journal of Statistics, 49(1), 116-142, 2022
  • Marginally Calibrated Deep Distributional Regression pdf

    N. Klein, D. J. Nott and M. S. Smith
    Journal of Computational and Graphical Statistics, 30(2), 467-483, 2021
  • Bayesian Variable Selection for Non-Gaussian Responses: A marginally-calibrated Copula Approach pdf

    N. Klein and M. S. Smith
    Biometrics, 77(3), 809-823, 2021
  • Bayesian Inference for Regression Copulas pdf

    M. S. Smith and N. Klein
    Journal of Business and Economic Statistics, 39(3), 712-728, 2021
  • Modelling Regional Patterns of Inefficiency: A Bayesian Approach to Geoadditive Panel Stochastic Frontier Analysis with an Application to Cereal Production in England and Wales pdf

    N. Klein, H. Herwartz and T. Kneib
    Journal of Econometrics, 214(2), 513-539, 2020
  • Implicit Copulas from Bayesian Regularized Regression Smoothers pdf

    N. Klein and M. S. Smith
    Bayesian Analysis, 14(4), 1143-1171, 2019
  • BAMLSS: Bayesian Additive Models for Location, Scale and Shape (and Beyond) pdf

    N. Umlauf, N. Klein and A. Zeileis
    Journal of Computational and Graphical Statistics, 27(3), 612-627, 2018
  • Bayesian Generalized Additive Models for Location, Scale and Shape for Zero-Inflated and Overdispersed Count Data pdf

    N. Klein, T. Kneib and S. Lang
    Journal of the American Statistical Association, 110(509), 405-419, 2015
  • Bayesian Structured Additive Distributional Regression with an Application to Regional Income Inequality in Germany pdf

    N. Klein, T. Kneib, S. Lang and A. Sohn
    Annals of Applied Statistics, 9(2), 1024-1052, 2015
  • Bayesian Conditional Transformation Models pdf

    M. Carlan, T. Kneib and N. Klein
    To appear in Journal of the American Statistical Association.
  • Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices pdf

    N. Klein, M. S. Smith and D. J. Nott
    To appear in Journal of Applied Econometrics.
  • Learning Causal Graphs in Manufacturing Domains Using Structural Equation Model

    M. Kertel, S. Harmeling, M. Pauly and N. Klein
    To appear in International Journal of Semantic Computing.
  • Estimating Uncertainty in Real Estate Valuation: A Multilevel Approach based on Distributional and Quantile Regression

    A. Razen, W. Brunauer, N. Klein, T. Kneib, S. Lang and N. Umlauf
    To appear in Statistical Modelling.
  • Boosting Multivariate Structured Additive Distributional Regression Models pdf

    A. Strömer, N. Klein, C. Staerk, H. Klinkhammer and A. Mayr
    To appear in Statistics in Medicine.
  • Semi-Structured Distributional Regression pdf

    D. Rügamer, C. Kolb and N. Klein
    To appear in The American Statistician.
  • Gaussian Process Responses in Distributional Regression: A versatile Model Class with an Application to Tree Growth Dynamics

    H. Riebl, N. Klein and T. Kneib
    To appear in Journal of the Royal Statistical Society, Series C.

Working Papers

  • Farm Structure and Environmental Context drive Farmers' Decisions on the Allocation of Ecological Focus Areas in Germany

    V. Alarcón-Segura, S. Roilo, A. Paulus, M. Beckmann, N. Klein and A. Cord, 2022
    Submitted. Available on request.
  • Anisotropic Multidimensional Smoothing using Bayesian Tensor Product P-Splines pdf

    P. Bach and N. Klein, 2022
  • MultiFlags: Multi-Class Size Recommendations for Fashion E-Commerce

    H. Boeddeker, N. Klein, L. Lefakis, A. Weffer, L. Karessli and M. Shirvany, 2022
    Submitted. Available on request.
  • Incorporating Actor Heterogeneity Into Large Network Models through Variational Approximations pdf

    N. Klein and G. Kauermann, 2022
  • Intergenerational Social Mobility in the United States: A Multivariate Analysis using Bayesian Distributional Regression

    A. März, N. Klein, T. Kneib and O. Mußhoff, 2022
    Submitted. Available on request.
  • A Multidimensional Approach is needed to better quantify Land-Use Intensity in Biodiversity Models

    S. Roilo, A. Paulus, V. Alarcón Segura, L. Kock, M. Beckmann, N. Klein and A. Cord, 2022
    Submitted. Available on request.
    • Informed Priors for Knowledge Integration in Trajectory Prediction pdf

      C. Schlauch, N. Klein and C. Wirth, 2022
      Submitted.
    • Accounting for Time Dependency in Meta-Analyses of Concordance Probability Estimates pdf

      M. Schmid, L. Weinhold, N. Klein and T. Fried, 2022
    • Distributional Adaptive Soft Regression Trees pdf

      N. Umlauf and N. Klein, 2022
      Submitted.
    • Scalable Estimation for Structured Additive Distributional Regression pdf

      N. Umlauf, J. Seiler, M. Wetscher, T. Simon, S. Lang and N. Klein, 2022
      Submitted.
    • Posterior Concentration Rates for Bayesian O'Sullivan Penalized Splines pdf

      P. Bach and N. Klein, 2021
    • Bayesian Effect Selection for Additive Quantile Regression with an Analysis to Air Pollution Thresholds pdf

      N. Klein and J. Mateu, 2021
      R& R Annals of Applied Statistics
    • Flexible Specification Testing in Semi-Parametric Quantile Regression Models pdf

      T. Kutzker, N. Klein and D. Wied, 2021
    • Bivariate Analysis of Birth Weight and Gestational Age depending on Environmental Exposures: Bayesian Distributional Regression with Copulas pdf

      J. Rathjens, A. Kolbe, J. Hölzer, K. Ickstadt and N. Klein, 2021
    • Approximate Bayesian Computation for Parameter Identification in Computational Mechanics

      M. G. R. Faes, N. Klein, M. Pauly, M. A. Valdebenito and M. A. Misraji, 2023
      Submitted to the 14th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP14.

Teaching

  • Bachelor's and Master's Theses

    We offer Bachelor's and Master's theses at the intersection of Statistics and Machine Learning. Should you be looking for a thesis or project in these areas, please see here for a list of available topics.

    A selection of completed theses at the chair can be found below.

      Master Theses
      • Analyzing Heat and Experienced Racial Segregation using Large-Scale Foot Traffic Data
      • A Python Implementation for the Structural Topic Model
      • Optimierung der Kraftwerkssteuerung mittel Reinforcement Learning unter Einsatz von kurzfristigen Ausgleichsenergiepreiseprognosen
      • Including Deep Neural Network Architectures into Multistage Intensity Models: An Application to Credit Risks
      • MultiFlags and LatentFlags: A Probabilistic Framework for Size Advice in Fashion E-Commerce
      • Interpretable Modelling of ICU Patients Remaining Length-of-Stay Distribution using Tabular Patient Data, Clinical Notes and Irregularly Spaced Clinical Measurements
      • Using Variational Inference to Estimate Structred Additive Distributional Regression Models
      • Elastic Full Procluster Means for Sparse and Irregular Curves
      • Reconstructing Multivariate Functional Data with Medical Applications
      • Investment Constraints in Southern Europe: A Spatial Econometric Analysis of World Bank Enterprise Surveys
      Bachelor Theses
      • Application of Regression Trees on Compositional Data Using European Parliament Election Results
      • Die Modellierung der COVID-19 Fallzahlen in Abhängigkeit von Strukturdaten zu Wetter und Bevölkerung in Berlin
      • Vergleich von Vorhersagemodellen zu Stornierungen von Hotelbuchungen
  • Lectures

    Advanced Bayesian Data Analysis
    LSF

    Lecture: Thursdays 10:00 - 12:00 (Mathetower E25)
    Exercise: Thursdays 12:00 - 14:00 (Mathetower E25)
    More details in first session (06.04.2023)

    Selected Topics in Data Science
    LSF
    (Please see LSF for the Moodle password)
    Lecture: Thursdays 14:00 - 16:00 (CDI/ZHB 120)
    Exercise: Tuesdays 10:00 - 12:00 (CDI/ZHB 120)
    More details in first session (06.04.2023)