2 papers
cs.LG2018
T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling
Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla +1
In this paper we propose a data augmentation method for time series with irregular sampling, Time-Conditional Generative Adversarial Network (T-CGAN). Our approach is based on Cond…
astro-ph.EP2018
Finding Asteroids Down the Back of the Couch: A Novel Approach to the Minor Planet Linking Problem
Matthew J. Holman, Matthew J. Payne, Paul Blankley +2
We present a novel approach to the minor planet linking problem. Our heliocentric transformation-and-propagation algorithm clusters tracklets at common epochs, allowing for the eff…