research
∙
06/03/2022
On Calibration of Graph Neural Networks for Node Classification
Graphs can model real-world, complex systems by representing entities an...
share
research
∙
12/15/2021
TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphs
Conventional static knowledge graphs model entities in relational data a...
research
∙
12/03/2021
Combining Sub-Symbolic and Symbolic Methods for Explainability
Similarly to other connectionist models, Graph Neural Networks (GNNs) la...
research
∙
11/25/2021
Demystifying Graph Neural Network Explanations
Graph neural networks (GNNs) are quickly becoming the standard approach ...
research
∙
10/28/2021
Generating Table Vector Representations
High-quality Web tables are rich sources of information that can be used...
research
∙
09/08/2021
Power to the Relational Inductive Bias: Graph Neural Networks in Electrical Power Grids
The application of graph neural networks (GNNs) to the domain of electri...
research
∙
08/02/2021
Learning Domain-Specific Edit Operations from Model Repositories with Frequent Subgraph Mining
Model transformations play a fundamental role in model-driven software d...
research
∙
05/17/2021
In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study
We report on a large-scale empirical study investigating the relevance o...
research
∙
03/18/2021
Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs
Biomedical knowledge graphs permit an integrative computational approach...
research
∙
07/10/2020
Integrating Logical Rules Into Neural Multi-Hop Reasoning for Drug Repurposing
The graph structure of biomedical data differs from those in typical kno...
research
∙
01/09/2020
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs
We propose a novel method for fact-checking on knowledge graphs based on...
research
∙
01/02/2020
