Search Results for author:
Found 2 papers, 1 papers with code
A Self-supervised Approach to Hierarchical Forecasting with Applications to Groupwise Synthetic Controls
When forecasting time series with a hierarchical structure, the existing state of the art is to forecast each time series independently, and, in a post-treatment step, to reconcile the time series in a way that respects the hierarchy (Hyndman et al., 2011; Wickramasuriya et al., 2018).
GANs for Biological Image Synthesis
In this paper, we propose a novel application of Generative Adversarial Networks (GAN) to the synthesis of cells imaged by fluorescence microscopy.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
