9 citations · 15 across the 3 of their papers we have counts for
8 papers
Interpretation of Natural Language Rules in Conversational Machine Reading
Marzieh Saeidi, Max Bartolo, Patrick Lewis +5
Most work in machine reading focuses on question answering problems where the answer is directly expressed in the text to read. However, many real-world question answering problems…
On Inductive Abilities of Latent Factor Models for Relational Learning
Théo Trouillon, Éric Gaussier, Christopher R. Dance +1
Latent factor models are increasingly popular for modeling multi-relational knowledge graphs. By their vectorial nature, it is not only hard to interpret why this class of models w…
Complex Embeddings for Simple Link Prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel +2
In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases. As in previous studies, we propose to sol…
Decomposing Real Square Matrices via Unitary Diagonalization
Théo Trouillon, Christopher R. Dance, Éric Gaussier +1
Diagonalization, or eigenvalue decomposition, is very useful in many areas of applied mathematics, including signal processing and quantum physics. Matrix decomposition is also a u…
A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion
Johannes Welbl, Guillaume Bouchard, Sebastian Riedel
Embedding-based Knowledge Base Completion models have so far mostly combined distributed representations of individual entities or relations to compute truth scores of missing link…
Approximate Inference with the Variational Holder Bound
Guillaume Bouchard, Balaji Lakshminarayanan
We introduce the Variational Holder (VH) bound as an alternative to Variational Bayes (VB) for approximate Bayesian inference. Unlike VB which typically involves maximization of a…