GitHub

An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection

TSB-UAD is a new open, end-to-end benchmark suite to ease the evaluation of univariate time-series anomaly detection methods. Overall, TSB-UAD contains 12686 time series with labeled anomalies ...
BMJ

Empirical evaluation of SUCRA-based treatment ranks in network meta-analysis: quantifying robustness using Cohen’s kappa

Objective To provide a framework for quantifying the robustness of treatment ranks based on Surface Under the Cumulative RAnking curve (SUCRA) in network meta-analysis (NMA) and investigating ...
IEEE

A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

Abstract: A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to ...
IEEE

Machine Learning for Univariate Time Series Imputation

Abstract: Missing data occur in almost real time series applications. Using incomplete data or ignoring missing values can cause inaccurate results and reduce system efficiency. Recovering missing ...