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.
Related
13.11.2025
Anne-Laure Boulesteix Among the World’s Most Cited Researchers
MCML PI Anne‑Laure Boulesteix named Highly Cited Researcher 2025 for cross-field work, among 17 LMU scholars recognized globally.
13.11.2025
Björn Ommer Featured in Frankfurter Rundschau
Björn Ommer highlights how Google’s new AI search mode impacts publishers, content visibility, and the diversity of online information.
13.11.2025
Fabian Theis Among the World’s Most Cited Researchers
Fabian Theis is named a Highly Cited Researcher 2025 for his work in mathematical modeling of biological systems.
13.11.2025
Explaining AI Decisions: Shapley Values Enable Smart Exosuits
AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.
