Julian Rodemann

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 20

Top Topics

Conditionally Independent

Gaussian Process

Top Venues

Publications

Julian Rodemann, Hannah Blocher
Partial Rankings of Optimizers. CoRR (2024)
Julian Rodemann, Thomas Augustin
Imprecise Bayesian optimization. Knowl. Based Syst. 300 (2024)
Julian Rodemann, Hannah Blocher
Partial Rankings of Optimizers. Tiny Papers @ ICLR (2024)
Julian Rodemann, Federico Croppi, Philipp Arens, Yusuf Sale, Julia Herbinger, Bernd Bischl, Eyke Hüllermeier, Thomas Augustin, Conor J. Walsh, Giuseppe Casalicchio
Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration. CoRR (2024)
Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera, Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers
How to Choose a Reinforcement-Learning Algorithm. CoRR (2024)
Malte Nalenz, Julian Rodemann, Thomas Augustin
Learning de-biased regression trees and forests from complex samples. Mach. Learn. 113 (6) (2024)
Stefan Dietrich, Julian Rodemann, Christoph Jansen
Semi-Supervised Learning guided by the Generalized Bayes Rule under Soft Revision. CoRR (2024)
Esteban Garces Arias, Julian Rodemann, Meimingwei Li, Christian Heumann, Matthias Aßenmacher
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text Generation. CoRR (2024)
Julian Rodemann
Towards Bayesian Data Selection. CoRR (2024)
Christoph Jansen, Georg Schollmeyer, Julian Rodemann, Hannah Blocher, Thomas Augustin
Statistical Multicriteria Benchmarking via the GSD-Front. CoRR (2024)
Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin
Robust statistical comparison of random variables with locally varying scale of measurement. UAI (2023)
Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin
Approximate Bayes Optimal Pseudo-Label Selection. CoRR (2023)
Julian Rodemann, Christoph Jansen, Georg Schollmeyer, Thomas Augustin
In all likelihoods: robust selection of pseudo-labeled data. ISIPTA (2023)
Julian Rodemann
Pseudo Label Selection is a Decision Problem. CoRR (2023)
Julian Rodemann, Christoph Jansen, Georg Schollmeyer, Thomas Augustin
In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning. CoRR (2023)
Christoph Jansen, Georg Schollmeyer, Hannah Blocher, Julian Rodemann, Thomas Augustin
Robust Statistical Comparison of Random Variables with Locally Varying Scale of Measurement. CoRR (2023)
Julian Rodemann, Jann Goschenhofer, Emilio Dorigatti, Thomas Nagler, Thomas Augustin
Approximately Bayes-optimal pseudo-label selection. UAI (2023)
Julian Rodemann, Thomas Augustin
Accounting for Gaussian Process Imprecision in Bayesian Optimization. IUKM (2022)
Julian Rodemann, Dominik Kreiss, Eyke Hüllermeier, Thomas Augustin
Levelwise Data Disambiguation by Cautious Superset Classification. SUM (2022)
Julian Rodemann, Thomas Augustin
Accounting for Gaussian Process Imprecision in Bayesian Optimization. CoRR (2021)