20 datasets found

Monthly data from the UK using the newly built database from Goulet Coulombe et al. (2021).

Quarterly US data based on McCracken and Ng (2020) and the popular FRED database from the Federal Reserve Bank of St-Louis.

The dataset used in this paper is a two-channel ECG signal, which is converted to trains of events using Lebesgue sampling.

The Electric Power Consumption dataset is a time series dataset.

The MODIS 16-day composite NDVI products from 2001 to 2018 were used to test the proposed reconstruction method.

Electricity, coal, gas, and fuel prices dataset for testing deep hedging strategies

Commodity prices dataset for testing state-of-the-art generative methods

A collection of multivariate time series with missing observations.

A multivariate time-series dataset that consists of hourly occupancy rates of lanes in San Francisco.

A multivariate time-series dataset that consists of temporal features and spatial features.

The UEA archive is a collection of multivariate time series datasets where classification is of importance.

The UCR archive is a collection of univariate time series datasets where classification is of importance.

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption,...

A synthetic univariate time series dataset created using a unique synthetic time series generator algorithm

UCR Time Series Archive is a collection of time series datasets from various domains. It is used for training and testing deep neural networks for time series classification tasks.

Long Short Term Memory Networks for Anomaly Detection in Time Series

Time series anomaly detection method based on VAE with re-Encoder and latent constraint network

The PTB-XL dataset consists of 21837 clinical 12-lead ECGs, each lasting 10 seconds, from 18885 patients.

The dataset contains energy data from the UCI Appliances energy prediction dataset with 28 features and noisy periodicity and correlation.

The dataset contains multivariate sinusoidal time-series with different frequencies and phases.