143 citations · 223 across the 5 of their papers we have counts for
5 papers
Designing an Interpretable Interface for Contextual Bandits
Andrew Maher, Matia Gobbo, Lancelot Lachartre +3
Contextual bandits have become an increasingly popular solution for personalized recommender systems. Despite their growing use, the interpretability of these systems remains a sig…
Batched Online Contextual Sparse Bandits with Sequential Inclusion of Features
Rowan Swiers, Subash Prabanantham, Andrew Maher
Multi-armed Bandits (MABs) are increasingly employed in online platforms and e-commerce to optimize decision making for personalized user experiences. In this work, we focus on the…
A Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets
Cheng Ye, Rowan Swiers, Stephen Bonner +1
The drug discovery and development process is a long and expensive one, costing over 1 billion USD on average per drug and taking 10-15 years. To reduce the high levels of attritio…
Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery
Stephen Bonner, Ian P Barrett, Cheng Ye +4
Knowledge Graphs (KG) and associated Knowledge Graph Embedding (KGE) models have recently begun to be explored in the context of drug discovery and have the potential to assist in…
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
Stephen Bonner, Ian P Barrett, Cheng Ye +5
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of…