Joint models for longitudinal and time-to-event data are commonly used in longitudinal studies to forecast disease trajectories over time. While there are many advantages to joint modeling, the standard forms suffer from limitations that arise from a fixed model specification, and computational difficulties when applied to high-dimensional datasets. In this paper, we propose a deep learning app...

in this paper, three-dimensional modeling of the fatigue crack growth profiles was performed in a simple riveted lap joint. simulation results showed that mode i was dominated on the one side of the plates and the crack straightly grew on this side, while the other side of the plates was in a mixed-mode condition and the crack propagation path was not straight on this side. afterward, the fract...

This paper proposes an iterative score-based generative model for solving the automatic colorization problem. Although unsupervised learning methods have shown capability to generate plausible color, inadequate exploration of detailed information and data dimensions still limit performance model. Considering that number samples in has influence on estimating target gradients gradient map posses...