881 citations · 1.7k across the 43 of their papers we have counts for
44 papers
Knowledge Hypergraph Embedding Meets Relational Algebra
Bahare Fatemi, Perouz Taslakian, David Vazquez +1
Embedding-based methods for reasoning in knowledge hypergraphs learn a representation for each entity and relation. Current methods do not capture the procedural rules underlying t…
Binarised Regression with Instance-Varying Costs: Evaluation using Impact Curves
Matthew Dirks, David Poole
Many evaluation methods exist, each for a particular prediction task, and there are a number of prediction tasks commonly performed including classification and regression. In bina…
Predicting Landslides Using Locally Aligned Convolutional Neural Networks
Ainaz Hajimoradlou, Gioachino Roberti, David Poole
Landslides, movement of soil and rock under the influence of gravity, are common phenomena that cause significant human and economic losses every year. Experts use heterogeneous fe…
Knowledge Hypergraphs: Prediction Beyond Binary Relations
Bahare Fatemi, Perouz Taslakian, David Vazquez +1
Knowledge graphs store facts using relations between two entities. In this work, we address the question of link prediction in knowledge hypergraphs where relations are defined on…
Improved Knowledge Graph Embedding using Background Taxonomic Information
Bahare Fatemi, Siamak Ravanbakhsh, David Poole
Knowledge graphs are used to represent relational information in terms of triples. To enable learning about domains, embedding models, such as tensor factorization models, can be u…
Structure Learning for Relational Logistic Regression: An Ensemble Approach
Nandini Ramanan, Gautam Kunapuli, Tushar Khot +5
We consider the problem of learning Relational Logistic Regression (RLR). Unlike standard logistic regression, the features of RLRs are first-order formulae with associated weight…