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A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, [1] [2] [3] which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one.
John Neulinger (April 26, 1924 - June 20, 1991) was a German-American psychologist and Professor Emeritus of psychology at City College of New York.Neulinger is best known for contributing a social psychological theory of leisure to the field of leisure studies. [1]
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Recreation is an activity of leisure, leisure being discretionary time. [1] The "need to do something for recreation" is an essential element of human biology and psychology . [ 2 ] Recreational activities are often done for enjoyment , amusement , or pleasure and are considered to be " fun ".
TV show producers are also releasing video clips from live TV, including promotional trailers and excerpts from shows on popular social media platforms, including Facebook, Instagram, Twitter and Snapchat in order to generate additional advertising revenue and increase Internet users' awareness of and interest in their show.
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The parameters of the neural network are therefore trained in a generative manner via MCMC-based maximum likelihood estimation: [6] the learning process follows an "analysis by synthesis" scheme, where within each learning iteration, the algorithm samples the synthesized examples from the current model by a gradient-based MCMC method (e.g ...
Analytical methods that analyse a given flow and show properties like streamlines, streaklines, and pathlines. The flow can either be given in a finite representation or as a smooth function. Texture advection methods that "bend" textures (or images) according to the flow. As the image is always finite (the flow through could be given as a ...