Thomas Augustin

About Thomas Augustin

Thomas Augustin, With an exceptional h-index of 27 and a recent h-index of 14 (since 2020), a distinguished researcher at Ludwig-Maximilians-Universität München, specializes in the field of Imprecise Probability, Partial Identification, Measurement Error, Decision Theory, Official Statistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration

Learning de-biased regression trees and forests from complex samples

Approximately Bayes-optimal pseudo-label selection

Consideration Set Sampling to Analyze Undecided Respondents

Multi-target decision making under conditions of severe uncertainty

An empirical study of prior-data conflicts in Bayesian neural networks

In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning

Interpreting Generalized Bayesian Inference by Generalized Bayesian Inference

Thomas Augustin Information

University

Position

Professor Department of Statistics (LMU)

Citations(all)

7007

Citations(since 2020)

3467

Cited By

4856

hIndex(all)

27

hIndex(since 2020)

14

i10Index(all)

49

i10Index(since 2020)

21

Email

University Profile Page

Ludwig-Maximilians-Universität München

Google Scholar

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Thomas Augustin Skills & Research Interests

Imprecise Probability

Partial Identification

Measurement Error

Decision Theory

Official Statistics

Top articles of Thomas Augustin

Title

Journal

Author(s)

Publication Date

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration

arXiv preprint arXiv:2403.04629

Julian Rodemann

Federico Croppi

Philipp Arens

Yusuf Sale

Julia Herbinger

...

2024/3/7

Learning de-biased regression trees and forests from complex samples

Machine Learning

Malte Nalenz

Julian Rodemann

Thomas Augustin

2024/1/8

Approximately Bayes-optimal pseudo-label selection

Julian Rodemann

Jann Goschenhofer

Emilio Dorigatti

Thomas Nagler

Thomas Augustin

2023/7/2

Consideration Set Sampling to Analyze Undecided Respondents

arXiv preprint arXiv:2307.14333

Dominik Kreiss

Thomas Augustin

2023/7/26

Multi-target decision making under conditions of severe uncertainty

Christoph Jansen

Georg Schollmeyer

Thomas Augustin

2023/5/19

An empirical study of prior-data conflicts in Bayesian neural networks

Alexander Marquardt

Julian Rodemann

Thomas Augustin

2023/7/11

In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning

arXiv preprint arXiv:2303.01117

Julian Rodemann

Christoph Jansen

Georg Schollmeyer

Thomas Augustin

2023/3/2

Interpreting Generalized Bayesian Inference by Generalized Bayesian Inference

Interpreting

Julian Rodemann

Thomas Augustin

Rianne de Heide

2023/7/11

Reflections on the Foundations of Probability and Statistics: Essays in Honor of Teddy Seidenfeld

Thomas Augustin

Fabio Gagliardi Cozman

Gregory Wheeler

2023/1/14

In all likelihoods: Robust selection of pseudo-labeled data

Julian Rodemann

Christoph Jansen

Georg Schollmeyer

Thomas Augustin

2023/7/10

Statistical comparisons of classifiers by generalized stochastic dominance

Journal of Machine Learning Research

Christoph Jansen

Malte Nalenz

Georg Schollmeyer

Thomas Augustin

2023

Robust statistical comparison of random variables with locally varying scale of measurement

Christoph Jansen

Georg Schollmeyer

Hannah Blocher

Julian Rodemann

Thomas Augustin

2023/7/2

Evaluating machine learning models in non-standard settings: An overview and new findings

Roman Hornung

Malte Nalenz

Lennart Schneider

Andreas Bender

Ludwig Bothmann

...

2023/10/23

Not all data are created equal: Lessons from sampling theory for adaptive machine learning

Julian Rodemann

Sebastian Fischer

Lennart Schneider

Malte Nalenz

Thomas Augustin

2022/12/13

Statistics with imprecise probabilities—a short survey

Uncertainty in Engineering Introduction to Methods and Applications

Thomas Augustin

2022

Learning from categorical data subject to non-random misclassification and non-response under prior quasi-near-ignorance using an imprecise Dirichlet model

Aziz Omar

Timo von Oertzen

Thomas Augustin

2022/7/4

Levelwise data disambiguation by cautious superset classification

Julian Rodemann

Dominik Kreiss

Eyke Hüllermeier

Thomas Augustin

2022/10/10

Nachruf Hans Schneeweiß

AStA Wirtschafts-und Sozialstatistisches Archiv

Thomas Augustin

Helmut Küchenhoff

Matthias Schmid

2022/6

Imprecise Learning from Misclassified and Incomplete Categorical Data with Unknown Error Structure

Aziz Omar

Thomas Augustin

2022/8/25

Information efficient learning of complexly structured preferences: Elicitation procedures and their application to decision making under uncertainty

International Journal of Approximate Reasoning

Christoph Jansen

Hannah Blocher

Thomas Augustin

Georg Schollmeyer

2022/5/1

See List of Professors in Thomas Augustin University(Ludwig-Maximilians-Universität München)

Co-Authors

H-index: 57
Anne-Laure Boulesteix

Anne-Laure Boulesteix

Ludwig-Maximilians-Universität München

H-index: 52
Thomas Kneib

Thomas Kneib

Georg-August-Universität Göttingen

H-index: 36
Gert de Cooman

Gert de Cooman

Universiteit Gent

H-index: 36
Frank Coolen

Frank Coolen

Durham University

H-index: 20
Matthias C. M. Troffaes

Matthias C. M. Troffaes

Durham University

H-index: 14
Marco E. G. V. Cattaneo

Marco E. G. V. Cattaneo

Universität Basel

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