INFORMER-WGAN: HIGH MISSING RATE TIME SERIES IMPUTATION BASED ON ADVERSARIAL TRAINING AND A SELF-ATTENTION MECHANISM

Informer-WGAN: High Missing Rate Time Series Imputation Based on Adversarial Training and a Self-Attention Mechanism

Missing observations in time series will distort the data characteristics, change the dataset expectations, high-order distances, and other statistics, and increase the difficulty of data analysis.Therefore, data imputation needs to be performed first.Generally, data imputation methods include statistical imputation, regression imputation, multiple

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Fitness Consequences of Innovation in Spotted Hyenas

Innovation is a well-studied cognitive phenomenon related to general intelligence and brain size.Innovative ability varies considerably within species remtavares.com and it is widely assumed that this variation must have important fitness consequences.However, direct evidence for a link between innovative ability and fitness has rarely been shown.P

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