arXiv (Cornell University)
Exploring Scalability in Large-Scale Time Series in DeepVATS framework
August 2024 • Inmaculada Santamaria-Valenzuela, Víctor Rodríguez-Fernández, David Camacho
Visual analytics is essential for studying large time series due to its ability to reveal trends, anomalies, and insights. DeepVATS is a tool that merges Deep Learning (Deep) with Visual Analytics (VA) for the analysis of large time series data (TS). It has three interconnected modules. The Deep Learning module, developed in R, manages the load of datasets and Deep Learning models from and to the Storage module. This module also supports models training and the acquisition of the embeddings from the latent space o…