22.07.2022
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)
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
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)
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
Related
©Joachim Wendler - stock-adobe.com
02.01.2026
MCML Researchers in Highly-Ranked Journals
We are excited to announce that MCML researchers have three papers published in highly-ranked journals in %!s(
18.12.2025
"See, Don’t Assume": Revealing and Reducing Gender Bias in AI
ICLR 2025 research led by Zeynep Akata’s team reveals and reduces gender bias in popular vision-language AI models.
16.12.2025
Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine
MCML PI Fabian Theis discusses AI-driven precision medicine and its growing impact on individualized healthcare and biomedical research.
16.12.2025
Gitta Kutyniok Featured in VDI Nachrichten on AI Ethics
Gitta Kutyniok discusses measurable criteria for ethical AI, promoting safe and responsible autonomous decision-making.