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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.
The academy also serves as an authority in informing and training teachers and legislators on navigating AI in education, namely generative AI which can generate high-quality text, images 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 ...
The generation effect is typically achieved in cognitive psychology experiments by asking participants to generate words from word fragments. [2] This effect has also been demonstrated using a variety of other materials, such as when generating a word after being presented with its antonym, [3] synonym, [1] picture, [4] arithmetic problems, [2] [5] or keyword in a paragraph. [6]
The worked-example effect is a learning effect predicted by cognitive load theory. [1] [full citation needed] Specifically, it refers to improved learning observed when worked examples are used as part of instruction, compared to other instructional techniques such as problem-solving [2] [page needed] and discovery learning.
An example of soft scaffolding in the classroom would be when a teacher circulates the room and converses with his or her students. [30] The teacher may question their approach to a difficult problem and provide constructive feedback to the students. According to Van Lier, this type of scaffolding can also be referred to as contingent scaffolding.
An example of this is looking up a phone number but forgetting it before being able to dial it into the phone. This is a common form of rote learning . Rote learning is learning or memorization by repetition, often without an understanding of the reasoning or relationships involved in the material that is learned. [ 2 ]