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PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series [article]

Jeha Paul, Bohlke-Schneider Michael, Mercado Pedro, Kapoor Shubham, Singh Nirwan Rajbir, Flunkert Valentin, Gasthaus Jan, Januschowski Tim
2022 arXiv   pre-print
In this paper we present PSA-GAN, a generative adversarial network (GAN) that generates long time series samples of high quality using progressive growing of GANs and self-attention.  ...  Realistic synthetic time series data of sufficient length enables practical applications in time series modeling tasks, such as forecasting, but remains a challenge.  ...  CONCLUSION We have presented PSA-GAN, a progressive growing time series GAN augmented with self-attention, that produces long realistic time series and improves downstream forecasting tasks that are challenging  ... 
arXiv:2108.00981v3 fatcat:bw5y7ss2affzdhnrujhptblldm

Pharmacology, pharmacogenetics, and clinical efficacy of 5-hydroxytryptamine type 3 receptor antagonists for postoperative nausea and vomiting

Kok-Yuen Ho, Tong J Gan
2006 Current Opinion in Anaesthesiology  
These differences account for differences in the duration of action and clinical efficacy of these agents.  ...  Acknowledgements We are grateful to Dr Mark Palazzo, Charing Cross Hospital, London, UK, for his valuable help in revising the manuscript.  ...  Hill RP, Lubarsky DA, Phillips-Bute B, Fortney JT, Creed MR, Glass PSA, Gan TJ: Cost-effectiveness of prophylactic antiemetic therapy with ondansetron, droperidol, or placebo.  ... 
doi:10.1097/01.aco.0000247340.61815.38 pmid:17093363 fatcat:arruy65u2jcjdjar2hqegatlaq