IEEE

Ranking Time-Frequency Contrastive Learning for Multivariate Time Series Classification

Abstract: For multivariate time series classification, current research predominantly focuses on contrastive learning to acquire suitable representations. Despite their successes in enhancing accuracy ...
IEEE

DCT-Based Channel Attention for Multivariate Time Series Classification

Abstract: This article introduces a novel DCT-based channel attention (DCA) mechanism for time series classification (TSC) using convolutional neural networks (CNNs). Traditional ...
Digital Journal

Chandrashekar Althati: Leading innovation in multivariate transaction classification

Opinions expressed by Digital Journal contributors are their own. “As an inventor, I’ve always believed that data holds the key to solving the most complex problems. My goal has been to create ...
Frontiers

Sparse Ordinal Logistic Regression and Its Application to Brain Decoding

Brain decoding with multivariate classification and regression has provided a powerful framework for characterizing information encoded in population neural activity. Classification and regression ...
Frontiers

Data analysis competition: connectivity and multivariate classification approaches

While there are a number of advanced data analysis techniques that allow us to embrace distributed electrophysiological activity measured by MEG, these tools are somewhat underexploited. This includes ...
GitHub

Multivariate classification dataset loading error

Thank you very much for disseminating openly your work and code. I am trying to reproduce the classification notebook. It seems there is a bug in the ClassificationDataset class when loading the ...