Invited Presentation at 1st CIKM 2020 Workshop on Combining Symbolic and Sub-Symbolic Methods and Their Applications (CSSA-CIKM 2020)

Learning With Temporal Knowledge Graphs

MCML PI Volker Tresp, Yunpu Ma and Zhen Han review recently developed learning-based algorithms for temporal knowledge graphs completion and forecasting. Knowledge graphs, also known as episodic or time-dependent knowledge graphs are large-scale event databases that describe temporally evolving multi-relational data.

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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.

Invited Presentation at 1st CIKM 2020 Workshop on Combining Symbolic and Sub-Symbolic Methods and Their Applications (CSSA-CIKM 2020)

Learning With Temporal Knowledge Graphs

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