Home | News

22.07.2022

Tiny logo
Teaser image to MCML at IJCAI-ECAI 2022

MCML at IJCAI-ECAI 2022

Three Accepted Papers (2 Main, and 1 Workshop)

Best paper track at the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence, Vienna, Austria, Jul 23-29, 2022

We are happy to announce that MCML researchers have contributed a total of 3 papers to IJCAI-ECAI 2022: 2 Main, and 1 Workshop papers. Congrats to our researchers!

Main Track (2 papers)

M. Ali • M. Berrendorf • M. Galkin • V. Thost • T. Ma • V. Tresp • J. Lehmann
Improving Inductive Link Prediction Using Hyper-Relational Facts (Extended Abstract).
IJCAI-ECAI 2022 - Best paper track at the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. DOI

E. Schede • J. Brandt • A. Tornede • M. WeverV. BengsE. Hüllermeier • K. Tierney
A Survey of Methods for Automated Algorithm Configuration.
IJCAI-ECAI 2022 - 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. Extended Abstract. DOI

Workshops (1 paper)

A. Klaß • S. M. Lorenz • M. W. Lauer-Schmaltz • D. RügamerB. Bischl • C. Mutschler • F. Ott
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift.
STRL 2022 @IJCAI-ECAI 2022 - Workshop on Spatio-Temporal Reasoning and Learningat the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence. Vienna, Austria, Jul 23-29, 2022. URL

#research #top-tier-work #bischl #huellermeier #ruegamer #tresp

Related

Tiny logo
Link to MCML at ICDAR 2026

28.08.2026

MCML at ICDAR 2026

MCML researchers are represented with 1 paper at ICDAR 2026.

Read more
Link to Transparency for global health aid

26.08.2026

Transparency for Global Health Aid

MCML PI Stefan Feuerriegel and his team use machine learning to uncover disparities in the global allocation of health aid.

Read more
Link to David Rügamer: We Need Uncertainty Quantification

25.08.2026

David Rügamer: We Need Uncertainty Quantification

MCML PI David Rügamer explains why uncertainty quantification is essential for building trustworthy AI and making informed decisions.

Read more
Link to Using Data Science to Personalize Depression Care

24.08.2026

Using Data Science to Personalize Depression Care

Five young researchers explore how data science can contribute to better healthcare as part of DSSGx Munich 2026, supported by MCML.

Read more
Link to Matthias Nießner Featured in Augsburger Allgemeine on Europe's AI Hub

17.08.2026

Matthias Nießner Featured in Augsburger Allgemeine on Europe's AI Hub

MCML PI Matthias Nießner is featured in Augsburger Allgemeine's coverage of London's rise as a leading European AI hub.

Read more
Back to Top