Center for Trustworthy Data Science and Security
Contact
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nadja.klein at
statistik.tu-dortmund.de |
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Office
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From April 2023, I will be professor for Uncertainty Quantification and Statistical Learning at the Research Center Trustworthy Data Science and Security (UA Ruhr) and the Department of Statistics (Technische Universität Dortmund) and am principal investigator in several research projects.
Feel free to follow us on Twitter!
Information for Students
- My office hours are by appointment.
- For details regarding available Bachelor's and Master's Theses, please see the corresponding teaching section.
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 |  |
Group Lead | ___________ |
- Dependence Modeling (since 2021)
- 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
- Biometrics (since 2022)
- Advances in Statistical Analysis (since 2020)
- Journal of Agricultural, Biological and Environmental Statistics (since 2019)
- Annals of Applied Statistics
- Bayesian Analysis
- Biometrical Journal
- Computational Statistics
- Computational Statistics and Data Analysis
- Journal of Applied Econometrics
- Journal of the American Statistical Association
- Journal of Computational and Graphical Statistics
- Journal of the Royal Statistical Society
- Scandinavian Journal of Statistics
- Statistical Methods in Medical Research
- Statistics and Computing
- Statistics in Medicine
- 11th Annual RCEA Bayesian Econometric Workshop (University of Melbourne, 03 - 04/07/2017)
- 4th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik (DAGStat, Georg-August-Universität Göttingen, 14 - 18/03/2016)
- 29th International Workshop on Statistical Modelling (Georg-August-Universität Göttingen, 13 - 18/07/2014)
- Organized Session: Recent Advances in Copula Regression at the 15th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics, London, 17 - 19/12/22)
- Invited Session: Recent Advances in Variational Inference Methods at the 16th World Meeting of the International Society for Bayesian Analysis (Montreal, 25/06 - 01/07/22)
- Organized Session: Advances in Bayesian Econometrics at the 14th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics, London, 18 - 20/12/21)
- Organized Session: Advances in Distributional Regression Models at the 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics, London, 16 - 18/12/19)
- Invited Session: Advanced Regression Modeling-Longitudinal Data and Mixed Models at 5th Joint Statistical Meeting of the Deutsche Arbeitsgemeinschaft Statistik (DAGStat, Ludwig-Maximilians-Universität Munich, 18 - 22/03/2019)
- Workshop Fairness, Explainability and Uncertainty of AI (Research Group AI, Junge Akademie, 19 - 20/09/22)
- Workshop Data Science meets Landscape Ecology (joint with Anna Cord, TU Dresden, Junge Akademie, 15/06/22)
- 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)
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
Associate Editor
Referee
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
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 |  |
PhD Student |
| Guillermo Briseno-Sanchez |  |
PhD Student |
| Tim-Moritz Bündert |  |
Research Assistant |
| Ekin Celikkan |  |
PhD Student |
| Clara Hoffmann |  |
PhD Student |
| Maarten Jung |  |
Research Assistant |
| Lucas Kock |  |
PhD Student |
| Victor Medina-Olivares, PhD |  |
Postdoctoral Researcher |
| Christian Schlauch |  |
PhD Student |
| Bettina Schmidt |  |
PhD Student |
| Michael Stanley Smith |  |
Mercator Fellow |
| Ivan Ustyuzhaninov |  |
Postdoctoral Researcher |
| 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.
- from 2023: DFG Research Unit Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (sub-project P5, sub-project P6)
- since 2021: Experiment (funded by the Volkswagenstiftung)
- since 2020: DFG individual grant (jointly with Andreas Mayr, University of Bonn)
- since 2019: Emmy Noether Research Group (funded by the DFG)
Publications
See my Google Scholar entries for a complete list. Below you find some key publications and recent working papers.
Selected Publications
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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
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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
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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
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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.
- 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
- 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
Master Theses
Bachelor Theses
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Lectures
Advanced Bayesian Data Analysis
Lecture: Thursdays 10:00 - 12:00 (Mathetower E25)
Exercise: Thursdays 12:00 - 14:00 (Mathetower E25)
More details in first session (06.04.2023)