1 citations · 1 across the 5 of their papers we have counts for
5 papers
Flexible Blood Glucose Control: Offline Reinforcement Learning from Human Feedback
Harry Emerson, Sam Gordon James, Matthew Guy +1
Reinforcement learning (RL) has demonstrated success in automating insulin dosing in simulated type 1 diabetes (T1D) patients but is currently unable to incorporate patient experti…
Unsupervised Optimisation of GNNs for Node Clustering
William Leeney, Ryan McConville
Graph Neural Networks (GNNs) can be trained to detect communities within a graph by learning from the duality of feature and connectivity information. Currently, the common approac…
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection
William Leeney, Ryan McConville
(1) The enhanced capability of Graph Neural Networks (GNNs) in unsupervised community detection of clustered nodes is attributed to their capacity to encode both the connectivity a…
A Framework for Exploring Federated Community Detection
William Leeney, Ryan McConville
Federated Learning is machine learning in the context of a network of clients whilst maintaining data residency and/or privacy constraints. Community detection is the unsupervised…
The Safety Challenges of Deep Learning in Real-World Type 1 Diabetes Management
Harry Emerson, Ryan McConville, Matthew Guy
Blood glucose simulation allows the effectiveness of type 1 diabetes (T1D) management strategies to be evaluated without patient harm. Deep learning algorithms provide a promising…