3 papers
cs.LG2026
Generative Model via Quantile Assignment
Georgi Hrusanov, Oliver Y. Chén, Julien S. Bodelet
Deep Generative models (DGMs) play two key roles in modern machine learning: (i) producing new information (e.g., image synthesis) and (ii) reducing dimensionality. However, tradit…
cs.LG2025
Physics-Informed Neural Koopman Machine for Interpretable Longitudinal Personalized Alzheimer's Disease Forecasting
Georgi Hrusanov, Duy-Thanh Vu, Duy-Cat Can +6
Early forecasting of individual cognitive decline in Alzheimer's disease (AD) is central to disease evaluation and management. Despite advances, it is as of yet challenging for exi…
cs.LG2025
Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction
Narmina Baghirova, Duy-Thanh Vũ, Duy-Cat Can +6
Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of cases. AD is associated with disru…