Scholar
Nadja Klein
Google Scholar ID: upS2UTIAAAAJ
Karlsruhe Institute of Technology
Statistical & Machine Learning
Bayesian Statistics & Computing
Regression
Deep Learning &
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
1,885
H-index
23
i10-index
49
Publications
20
Co-authors
30
list available
Contact
Email
kleinlabtrello@gmail.com
GitHub
Open ↗
LinkedIn
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Publications
16 items
Semi-structured multi-state delinquency model for mortgage default
2026
Cited
0
Scalable and Robust Spatial Prediction via Multi-Resolution Ensembles of Predictive Processes
2026
Cited
0
Scalable Learning of Multivariate Distributions via Coresets
2026
Cited
0
Depth as Prior Knowledge for Object Detection
2026
Cited
0
Copula-based models for spatially dependent cylindrical data
2026
Cited
0
Bayesian Additive Regression Tree Copula Processes for Scalable Distributional Prediction
2026
Cited
0
BaGGLS: A Bayesian Shrinkage Framework for Interpretable Modeling of Interactions in High-Dimensional Biological Data
2025
Cited
0
Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
2025
Cited
0
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Resume (English only)
Academic Achievements
Publications, books, editorials, and supplementary materials are available on her webpage.
Research Experience
Involved in several research projects.
Background
Leads the research group on Methods for Big Data; teaches graduate courses in Bayesian statistics and machine learning.
Miscellany
Welcomes applications for PhDs and Postdocs, especially those with an interest in probabilistic learning & methods for big data.
Co-authors
30 total
Thomas Kneib
Chair of Statistics, Georg-August-University Göttingen
Co-author 2
Nikolaus Umlauf
Universität Innsbruck
Co-author 4
David Nott
Associate Professor of Statistics, National University of Singapore
Michael Stanley Smith
Chair of Management (Econometrics), Melbourne Business School, University of Melbourne
David Rügamer
Professor at LMU Munich, PI at Munich Center for Machine Learning
Achim Zeileis
Universität Innsbruck, Faculty of Economics and Statistics
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