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An embedding, or a smooth embedding, is defined to be an immersion that is an embedding in the topological sense mentioned above (i.e. homeomorphism onto its image). [ 4 ] In other words, the domain of an embedding is diffeomorphic to its image, and in particular the image of an embedding must be a submanifold .
Peter Worley argues that this is a false assumption. This is based on Worley's central arguments that there are two different kinds of open and closed questions: grammatical and conceptual. He argues that educational practitioners should be aiming for questions that are "grammatically closed, but conceptually open". [2]
In linguistics, center embedding is the process of embedding a phrase in the middle of another phrase of the same type. This often leads to difficulty with parsing which would be difficult to explain on grammatical grounds alone. The most frequently used example involves embedding a relative clause inside another one as in:
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis . Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [ 1 ]
The notion of a closed immersion is local in the sense that f is a closed immersion if and only if for some (equivalently every) open covering = the induced map : is a closed immersion. [ 5 ] [ 6 ] If the composition Z → Y → X {\displaystyle Z\to Y\to X} is a closed immersion and Y → X {\displaystyle Y\to X} is separated , then Z → Y ...
In practice however, BERT's sentence embedding with the [CLS] token achieves poor performance, often worse than simply averaging non-contextual word embeddings. SBERT later achieved superior sentence embedding performance [8] by fine tuning BERT's [CLS] token embeddings through the usage of a siamese neural network architecture on the SNLI dataset.
Embodied embedded cognition (EEC) is a philosophical theoretical position in cognitive science, closely related to situated cognition, embodied cognition, embodied cognitive science and dynamical systems theory. The theory states that intelligent behaviour emerges from the interplay between brain, body and world. [1]
Visual object recognition refers to the ability to identify the objects in view based on visual input. One important signature of visual object recognition is "object invariance", or the ability to identify objects across changes in the detailed context in which objects are viewed, including changes in illumination, object pose, and background context.