Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches

Mathematics, Engineering, Information Science, Computer Science, Artificial Intelligence,
Stochastic Markovian Jump Systems   Wiener Noise   Poisson Noise   Reinforcement Learning   Optimal Control   Policy Iteration Algorithm   Numerical Verification  

Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches Academic Context In modern control theory, optimal control is a crucial research field, aiming to design an optimal control strategy under various constraints for dynamic systems to minimize a given cost function. For stochasti...

Toward Optimal Disease Surveillance with Graph-Based Active Learning

Mathematics, Information Science, Medicine, Environmental and Public Health,
disease surveillance   active learning   network dynamics   epidemiology   public health  

Toward Optimal Disease Surveillance with Graph-Based Active Learning Academic Background With the acceleration of globalization, the speed and scope of infectious disease transmission have significantly increased. How to effectively monitor and control the spread of infectious diseases has become a critical issue in public health. Traditional disea...

Basis Restricted Elastic Shape Analysis Framework for Surfaces

Mathematics, Physics, Mechanics, Information Science, Computer Science, Artificial Intelligence,
Elastic Shape Analysis   Surface Meshes   Geometric Deep Learning   Riemannian Shape Metrics   Human Body Analysis   Shape Registration   Random Shape Generation  

# Basis Restricted Elastic Shape Analysis on the Space of Unregistered Surfaces ## Introduction Analyzing three-dimensional (3D) surfaces has become increasingly important in computer vision, driven by the emergence of high-accuracy 3D scanning devices. These devices have significantly increased the availability of 3D data, enabling applications in...

An Adaptive and Robust Method for Multi-Trait Analysis of Genome-Wide Association Studies Using Summary Statistics

Mathematics, Life Sciences, Genetics,
Multi-Trait Analysis   Genome-Wide Association Studies   Summary Statistics   Computational Efficiency   Mathematical Methods   Brain Imaging Phenotypes   Genetic Variants  

Adaptive Robust Method for Multi-trait Genome-wide Association Studies Abstract: Genome-wide association studies (GWAS) over the past decade have identified thousands of genetic variants associated with human traits or diseases. However, the heritability of many traits remains largely unexplained. Traditional single-trait analysis methods are overl...

Bayesian Tensor Modeling for Image-Based Classification of Alzheimer's Disease

Mathematics, Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
Alzheimer's disease   Bayesian tensor modeling   logistic regression   support vector machines   neuroimaging analysis  

Image Classification Based on Bayesian Tensor Modeling for Alzheimer’s Disease Introduction Neuroimaging research is a crucial component of contemporary neuroscience, significantly enhancing our understanding of brain structure and function. Through these non-invasive visualization techniques, researchers can more accurately predict the risk of cer...