6 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
On the Limits of Maximal Coding Rate Reduction for Out-of-Distribution Generalisation
Menghui Zhou, Gaoshan Bi, Vitaveska Lanfranchi +1
Substantial efforts have been devoted to making deep learning objectives, representations, and architectures interpretable, with the goal of improving the safety, robustness, and g…
DeMMO: Longitudinal and Cross-Disease Modelling of Digital Mobility Outcomes via Multi-Task Learning
Menghui Zhou, Zhipeng Yuan, Vitaveska Lanfranchi +1
Digital mobility outcomes (DMOs) derived from wearable sensors characterise mobility in daily life and offer a promising means of monitoring disease progression. However, existing…
Multi-Task Learning with Feature-Similarity Laplacian Graphs for Predicting Alzheimer's Disease Progression
Zixiang Xu, Menghui Zhou, Jun Qi +3
Alzheimer's Disease (AD) is the most prevalent neurodegenerative disorder in aging populations, posing a significant and escalating burden on global healthcare systems. While Multi…
Spatio-Temporal Similarity Measure based Multi-Task Learning for Predicting Alzheimer's Disease Progression using MRI Data
Xulong Wang, Yu Zhang, Menghui Zhou +3
Identifying and utilising various biomarkers for tracking Alzheimer's disease (AD) progression have received many recent attentions and enable helping clinicians make the prompt de…