MCML at UAI 2021

One Accepted Paper

Conference on Uncertainty in Artificial Intelligence, Virtual, Jul 27-29, 2021

We are happy to announce that MCML researchers have contributed a total of 1 paper to UAI 2021. Congrats to our researchers!

Main Track (1 paper)

Y. Wang • Y. Shen • D. Cremers
Explicit pairwise factorized graph neural network for semi-supervised node classification.
UAI 2021 - Conference on Uncertainty in Artificial Intelligence. Virtual, Jul 27-29, 2021. URL

#research #top-tier-work #cremers

Subscribe to RSS News feed

02.06.2026

Benjamin Lange: The Real Risk of AI Agents Is Manipulation Through Kindness

MCML Junior Research Group Leader Benjamin Lange examines how trust in AI agents can itself become a source of risk.

02.06.2026

MCML at CVPR 2026

MCML researchers are represented with 28 papers at CVPR 2026 (26 Main, and 2 Workshops).

29.05.2026

MCML at ICRA 2026

MCML researchers are represented with 4 papers at ICRA 2026 (3 Main, and 1 Workshop).

28.05.2026

Zeynep Akata: To Trust AI, We Need to Understand What Goes on Behind the Scenes

MCML PI Zeynep Akata explains that to trust AI, we must understand its inner workings, address foundation model bias, and make explainability central.

27.05.2026

Medical Diagnoses: How AI Explanations Help Doctors

Stefan Feuerriegel shows that AI models can improve diagnostic accuracy in radiology – but how the AI explains its recommendations is crucial.

MCML at UAI 2021

One Accepted Paper

Conference on Uncertainty in Artificial Intelligence, Virtual, Jul 27-29, 2021

Main Track (1 paper)

Related