1 citations · 1 across the 2 of their papers we have counts for
4 papers
Different Corruptions, Different Signals: Uncertainty and Loss in Federated Data Quality
Bradley Scott, Zeqi Luo, Edmond S. L. Ho
Federated learning (FL) data corruption can affect either inputs or labels, but it remains unclear whether input-conditional uncertainty and prediction-label loss expose these corr…
SWIM: Compact Environment Representation for Reinforcement Learning Human Swimming
Binglun Wang, Edmond S. L. Ho, Doğa Yılmaz +2
Deep reinforcement learning (RL) has driven rapid progress in physically-based motion generation, yet synthesizing robust motion policies in dense fluid environments (e.g. swimming…
CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network
Reza Akbari Movahed, Abuzar Rezaee, Arezoo Zakeri +3
Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnormalities. Existing methods often…
UDF-GMA: Uncertainty Disentanglement and Fusion for General Movement Assessment
Zeqi Luo, Ali Gooya, Edmond S. L. Ho
General movement assessment (GMA) is a non-invasive tool for the early detection of brain dysfunction through the qualitative assessment of general movements, and the development o…