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.

Learn more

#research #tresp

Subscribe to RSS News feed

20.03.2026

MCML Reaches H-Index of 100

MCML reaches an h-index of 100, marking a milestone achieved through years of collaboration with LMU Munich, TUM, and research partners worldwide.

19.03.2026

Teaching Models to Say ‘I’m Not Sure’

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

12.03.2026

Frauke Kreuter becomes AAAS Fellow

MCML PI Frauke Kreuter has been elected a Fellow of the American Association for the Advancement of Science (AAAS).

12.03.2026

MCML Members Receive Best Paper Award at GOR 2026

Christoph Kern and Jan Simson received the Best Paper Award at the GOR 2026 Conference in Cologne together with Fiona Draxler and Samuel Mehr.

12.03.2026

MCML Members Receive Honourable Mention at CHI 2026

MCML PI Enkelejda Kasneci and MCML Junior Member Ka Hei Carrie Lau have received an Honourable Mention Award at CHI 2026 for their paper.

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

Related