Julian Rodemann

According to our database, Julian Rodemann authored at least 31 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Self-Reinforcing Controllable Synthesis of Rare Relational Data via Bayesian Calibration.

Chongsheng Zhang, Hao Wang, Zelong Yu, Esteban Garces Arias, Julian Rodemann, Zhanshuo Zhang, Qilong Li, Gaojuan Fan, Krikamol Muandet, Christian Heumann

CoRR, April, 2026

Quantification of Credal Uncertainty: A Distance-Based Approach.

Xabier Gonzalez-Garcia, Siu Lun Chau, Julian Rodemann, Michele Caprio, Krikamol Muandet, Humberto Bustince, Sébastien Destercke, Eyke Hüllermeier, Yusuf Sale

CoRR, March, 2026

Incentive Aware AI Regulations: A Credal Characterisation.

Anurag Singh, Julian Rodemann, Rajeev Verma, Siu Lun Chau, Krikamol Muandet

CoRR, March, 2026

Beyond Arrow: From Impossibility to Possibilities in Multi-Criteria Benchmarking.

Polina Gordienko, Christoph Jansen, Julian Rodemann, Georg Schollmeyer

CoRR, February, 2026

Performative Learning Theory.

Julian Rodemann, Unai Fischer Abaigar, James Bailie, Krikamol Muandet

CoRR, February, 2026

Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification.

Julian Rodemann, Alexander Marquard, Thomas Augustin, Michele Caprio

Trans. Mach. Learn. Res., 2026

2025

The Geometry of Creative Variability: How Credal Sets Expose Calibration Gaps in Language Models.

Esteban Garces Arias, Julian Rodemann, Christian Heumann

CoRR, September, 2025

Generalization Bounds and Stopping Rules for Learning with Self-Selected Data.

Julian Rodemann, James Bailie

CoRR, May, 2025

A Statistical Case Against Empirical Human-AI Alignment.

Julian Rodemann, Esteban Garces Arias, Christoph Luther, Christoph Jansen, Thomas Augustin

CoRR, February, 2025

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration for Exosuit Personalization.

Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Applied Data Science Track, 2025

Statistical Multicriteria Evaluation of LLM-Generated Text.

Esteban Garces Arias, Hannah Blocher, Julian Rodemann, Matthias Aßenmacher, Christoph Jansen

Proceedings of the 18th International Natural Language Generation Conference, 2025

GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation.

Yuanhao Ding, Esteban Garces Arias, Meimingwei Li, Julian Rodemann, Matthias Aßenmacher, Danlu Chen, Gaojuan Fan, Christian Heumann, Chongsheng Zhang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024

Learning de-biased regression trees and forests from complex samples.

Malte Nalenz, Julian Rodemann, Thomas Augustin

Mach. Learn., June, 2024

Imprecise Bayesian optimization.

Julian Rodemann, Thomas Augustin

Knowl. Based Syst., 2024

Towards Better Open-Ended Text Generation: A Multicriteria Evaluation Framework.

Esteban Garces Arias, Hannah Blocher, Julian Rodemann, Meimingwei Li, Christian Heumann, Matthias Aßenmacher

CoRR, 2024

How to Choose a Reinforcement-Learning Algorithm.

Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera, Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers

CoRR, 2024

Towards Bayesian Data Selection.

Julian Rodemann

CoRR, 2024

Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision.

Stefan Dietrich, Julian Rodemann, Christoph Jansen

CoRR, 2024

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration.

Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio

CoRR, 2024

Reciprocal Learning.

Julian Rodemann, Christoph Jansen, Georg Schollmeyer

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Statistical Multicriteria Benchmarking via the GSD-Front.

Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Partial Rankings of Optimizers.

Julian Rodemann, Hannah Blocher

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation.

Esteban Garces Arias, Julian Rodemann, Meimingwei Li, Christian Heumann, Matthias Aßenmacher

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Pseudo Label Selection is a Decision Problem.

Julian Rodemann

CoRR, 2023

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

Julian Rodemann, Christoph Jansen, Georg Schollmeyer, Thomas Augustin

CoRR, 2023

Approximate Bayes Optimal Pseudo-Label Selection.

Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin

CoRR, 2023

Approximately Bayes-optimal pseudo-label selection.

Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin

Proceedings of the Uncertainty in Artificial Intelligence, 2023

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

Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin

Proceedings of the Uncertainty in Artificial Intelligence, 2023

In all likelihoods: robust selection of pseudo-labeled data.

Julian Rodemann, Christoph Jansen, Georg Schollmeyer, Thomas Augustin

Proceedings of the International Symposium on Imprecise Probability: Theories and Applications, 2023

2022

Levelwise Data Disambiguation by Cautious Superset Classification.

Julian Rodemann, Dominik Kreiss, Eyke Hüllermeier, Thomas Augustin

Proceedings of the Scalable Uncertainty Management - 15th International Conference, 2022

Accounting for Gaussian Process Imprecision in Bayesian Optimization.

Julian Rodemann, Thomas Augustin

Proceedings of the Integrated Uncertainty in Knowledge Modelling and Decision Making, 2022