10 citations · 26 across the 8 of their papers we have counts for
6 papers · 1 filter
Generating Table Vector Representations
Aneta Koleva, Martin Ringsquandl, Mitchell Joblin +1
High-quality Web tables are rich sources of information that can be used to populate Knowledge Graphs (KG). The focus of this paper is an evaluation of methods for table-to-class a…
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…
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…
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing
Yushan Liu, Marcel Hildebrandt, Mitchell Joblin +2
The graph structure of biomedical data differs from those in typical knowledge graph benchmark tasks. A particular property of biomedical data is the presence of long-range depende…
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs
Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma +3
We propose a novel method for fact-checking on knowledge graphs based on debate dynamics. The underlying idea is to frame the task of triple classification as a debate game between…
Reasoning on Knowledge Graphs with Debate Dynamics
Marcel Hildebrandt, Jorge Andres Quintero Serna, Yunpu Ma +3
We propose a novel method for automatic reasoning on knowledge graphs based on debate dynamics. The main idea is to frame the task of triple classification as a debate game between…