8 citations · 13 across the 13 of their papers we have counts for
3 papers · 1 filter
On the Aggregation of Rules for Knowledge Graph Completion
Patrick Betz, Stefan Lüdtke, Christian Meilicke +1
Rule learning approaches for knowledge graph completion are efficient, interpretable and competitive to purely neural models. The rule aggregation problem is concerned with finding…
Towards Machine Learning-based Fish Stock Assessment
Stefan Lüdtke, Maria E. Pierce
The accurate assessment of fish stocks is crucial for sustainable fisheries management. However, existing statistical stock assessment models can have low forecast performance of r…
Leveraging Planning Landmarks for Hybrid Online Goal Recognition
Nils Wilken, Lea Cohausz, Johannes Schaum +3
Goal recognition is an important problem in many application domains (e.g., pervasive computing, intrusion detection, computer games, etc.). In many application scenarios it is imp…