11 citations · 55 across the 12 of their papers we have counts for
5 papers · 1 filter
TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs
Yushan Liu, Yunpu Ma, Marcel Hildebrandt +2
Conventional static knowledge graphs model entities in relational data as nodes, connected by edges of specific relation types. However, information and knowledge evolve continuous…
Learning through structure: towards deep neuromorphic knowledge graph embeddings
Victor Caceres Chian, Marcel Hildebrandt, Thomas Runkler +1
Computing latent representations for graph-structured data is an ubiquitous learning task in many industrial and academic applications ranging from molecule synthetization to socia…
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids
Martin Ringsquandl, Houssem Sellami, Marcel Hildebrandt +4
The application of graph neural networks (GNNs) to the domain of electrical power grids has high potential impact on smart grid monitoring. Even though there is a natural correspon…
Graphhopper: Multi-Hop Scene Graph Reasoning for Visual Question Answering
Rajat Koner, Hang Li, Marcel Hildebrandt +3
Visual Question Answering (VQA) is concerned with answering free-form questions about an image. Since it requires a deep semantic and linguistic understanding of the question and t…
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
Yushan Liu, Marcel Hildebrandt, Mitchell Joblin +3
Biomedical knowledge graphs permit an integrative computational approach to reasoning about biological systems. The nature of biological data leads to a graph structure that differ…