8 citations · 11 across the 12 of their papers we have counts for
3 papers · 1 filter
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive Modelling
Alexander Capstick, Rahul G. Krishnan, Payam Barnaghi
Large language models (LLMs) acquire a breadth of information across various domains. However, their computational complexity, cost, and lack of transparency often hinder their dir…
Enabling Regional Explainability by Automatic and Model-agnostic Rule Extraction
Yu Chen, Tianyu Cui, Alexander Capstick +2
In Explainable AI, rule extraction translates model knowledge into logical rules, such as IF-THEN statements, crucial for understanding patterns learned by black-box models. This c…
Representation Learning of Daily Movement Data Using Text Encoders
Alexander Capstick, Tianyu Cui, Yu Chen +1
Time-series representation learning is a key area of research for remote healthcare monitoring applications. In this work, we focus on a dataset of recordings of in-home activity f…