Time Series Classifier

Time series classification (TSC) focuses on automatically assigning labels to sequential data, a crucial task across diverse fields. Recent research emphasizes developing more accurate and efficient classifiers, with a strong focus on deep learning architectures like Transformers and Convolutional Neural Networks, often combined with Recurrent Neural Networks to capture both local and global patterns within the data. Furthermore, there's a growing interest in improving the interpretability of these models, leading to the development of methods that provide insights into their decision-making processes, and in comparing the performance of sophisticated models against simpler baselines. This work has significant implications for applications ranging from healthcare and finance to environmental monitoring and energy management.