15.10.2020
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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01.07.2026
MCML at ACL 2026
MCML researchers are represented with 36 papers at ACL 2026 (20 Main, 15 Findings, and 1 Workshop).
30.06.2026
MCML Junior Members Featured in BR Abendschau
LMU researchers are putting different large language models head-to-head to find out which one delivers the most accurate predictions.
