MCML at KDD 2024

Two Accepted Papers

We are happy to announce that MCML researchers have contributed a total of 2 papers to KDD 2024. Congrats to our researchers!

T. Decker • A. Koebler • M. Lebacher • I. Thon • V. Tresp • F. Buettner
Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance.
KDD 2024 - 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Barcelona, Spain, Aug 25-29, 2024. DOI

M. Kuzmanovic • D. Frauen • T. Hatt • S. Feuerriegel
Causal Machine Learning for Cost-Effective Allocation of Development Aid.
KDD 2024 - 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Barcelona, Spain, Aug 25-29, 2024. DOI

10.03.2026

Reinhard Heckel Featured in FAZ

MCML PI Reinhard Heckel, featured in FAZ, explains how better data boosts AI performance and reduces bias.

05.03.2026

Foundations of Diffusion: One Map for Images and Text

Unified diffusion theory for images and text, bridging continuous and discrete models in one clear framework for generative AI.

05.03.2026

Matthias Althoff Featured in VentureCapital Magazin

MCML PI Matthias Althoff was featured in VentureCapital Magazin in connection with TUM spin-off Sitegeist.

05.03.2026

MCML at WACV 2026

MCML researchers are represented with 9 papers at WACV 2026.

05.03.2026

Sven Nyholm Featured in Big Think

MCML PI Sven Nyholm reflects on how AI convenience may reduce effort, skill development, and meaningful human achievement.