4 papers
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…
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…
OPTIMUS: Predicting Multivariate Outcomes in Alzheimer's Disease Using Multi-modal Data amidst Missing Values
Christelle Schneuwly Diaz, Duy-Thanh Vu, Julien Bodelet +7
Alzheimer's disease, a neurodegenerative disorder, is associated with neural, genetic, and proteomic factors while affecting multiple cognitive and behavioral faculties. Traditiona…
Statistical Quantile Learning for Large, Nonlinear, and Additive Latent Variable Models
Julien Bodelet, Guillaume Blanc, Jiajun Shan +2
The studies of large-scale, high-dimensional data in fields such as genomics and neuroscience have injected new insights into science. Yet, despite advances, they are confronting s…