Deep Learning

PyKale: an ML Library in PyTorch Ecosystem

Make machine learning more accessible to interdisciplinary research by bridging gaps between data, software, and end users

Haiping Lu, Xianyuan Liu, Robert Turner, Shuo Zhou, Peizhen Bai, Raivo Koot, Lawrence Schobs

PyKale: an ML Library in PyTorch Ecosystem

Uncertainty Est. for Landmark Localisation

Quantify the uncertainty in automatic anatomical landmark localisation

Lawrence Schobs, Andrew Swift, Haiping Lu

Uncertainty Est. for Landmark Localisation

Low-Bias Evaluation of Drug-Target Interaction

Hierarchical clustering split for low-bias evaluation of drug-target interaction prediction

Peizhen Bai, Bino John, Haiping Lu

Low-Bias Evaluation of Drug-Target Interaction

Human-In-The-Loop DL for Cardiac CT/MRI

Interactively trained ‘human-in-the-loop’ deep learning to improve cardiac CT/MRI assessment for accurate therapy response and mortality prediction

Andrew Swift, Haiping Lu

Human-In-The-Loop DL for Cardiac CT/MRI

Learnable GCN Aggregator

A feature-importance-aware and robust aggregator for graph convolutional networks (GCNs)

Li Zhang, Haiping Lu

Learnable GCN Aggregator