Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
Abstract: Multivariate time series anomaly detection (MTSAD) plays a crucial role in the Internet of Things (IoT) to identify device malfunction or system attacks. Graph neural networks (GNN) are ...
Abstract: Representing and exploiting multivariate signals requires capturing relations between variables, which we can represent by graphs. Graph dictionaries allow to describe complex relational ...
Detecting anomalies in multivariate time series (MTS) is essential for maintaining system safety in industrial environments. Due to the challenges associated with acquiring labeled data, unsupervised ...
The final, formatted version of the article will be published soon. Continuous traumatic stress has wide-ranging implications for important life outcomes across multiple domains. We present the design ...
Purpose: This study aimed to develop a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NAC) in patients with Human Epidermal Growth Factor Receptor 2 (HER2)-low breast cancer, ...
Mathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results