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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.
Because working memory is thought to influence g f, then training to increase the capacity of working memory could have a positive impact on g f. Some researchers, however, question whether the results of training interventions to enhance g f are long-lasting and transferable, especially when these techniques are used by healthy children and ...
Analogously, a classifier based on a generative model is a generative classifier, while a classifier based on a discriminative model is a discriminative classifier, though this term also refers to classifiers that are not based on a model. Standard examples of each, all of which are linear classifiers, are: generative classifiers:
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
By equipping the generative model with hidden states that model control, policies (control sequences) that minimise variational free energy lead to high utility states. [ 51 ] Neurobiologically, neuromodulators such as dopamine are considered to report the precision of prediction errors by modulating the gain of principal cells encoding ...
The generation effect has been found in studies using free recall, cued recall, and recognition tests. [3] In one study, the subject was provided with a stimulus word, the first letter of the response, and a word relating the two. For example, with the rule of the opposite, the stimulus word "hot", and the letter "c", the word cold would be ...
Stock and flow diagrams - a way to quantify the structure of a dynamic system; These methods allow showing a mental model of a dynamic system, as an explicit, written model about a certain system based on internal beliefs. Analyzing these graphical representations has been an increasing area of research across many social science fields. [9]
Studies have shown that short-term memory and long-term memory are two distinct processes that emphasize different levels of activation in the brain among different cortical areas. Furthermore, the rate of decay is much faster in short-term memory as opposed to long-term memory. The OSCAR model in particular does not account for this phenomenon.