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The brain doesn't merely register time—it structures it, according to new research from the Kavli Institute for Systems Neuroscience published in Science.

CSTS: A comprehensive benchmark for evaluating correlation structure discovery in time series data. This repository contains the code for generating synthetic time series with controlled correlation ...

Time-series data—measurements collected over time like stock prices or heart rates—plays a vital role in AI forecasting systems across industries. As these systems advance, the need for time-series ...

Time series data refers to a sequence of data points collected or recorded at regular time intervals. This type of data is prevalent across various domains, such as economics, weather, health, and ...

Learn about the factors that affect the efficiency of data structures for time-series data, and compare the pros and cons of relational, NoSQL, and specialized databases.

We generate dynamic hypergraph structures from time series data using the K-Nearest Neighbors method. Then a dynamic hypergraph structure learning module is used to optimize the hypergraph structure ...