T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling

2 code implementations • 20 Nov 2018 • Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, Ryan Janssen

Results show that classifiers trained on T-CGAN-generated data perform the same as classifiers trained on real data, even with very short time series and small training sets.

Data Augmentation Generative Adversarial Network +2