4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 4 cited
Visual Evaluation of Generative Adversarial Networks for Time Series Data
Hiba Arnout, Johannes Kehrer, Johanna Bronner +1
A crucial factor to trust Machine Learning (ML) algorithm decisions is a good representation of its application field by the training dataset. This is particularly true when parts…
cs.HC2019
Looking beyond the horizon: Evaluation of four compact visualization techniques for time series in a spatial context
Manuel Dahnert, Alexander Rind, Wolfgang Aigner +1
Visualizing time series in a dense spatial context such as a geographical map is a challenging task, which requires careful balance between the amount of depicted data and perceptu…