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A distributed, developmental model of word recognition and naming.
Results are discussed with regard to the Cohort model of word recognition.
We have reconsidered the patient data within the framework of an existing connectionist model of word recognition and spatial attention.
We describe a computational model of word learning that solves these two inference problems in parallel, rather than relying exclusively on either the inferred meanings of utterances or cross-situational word-meaning associations.
He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, neural network dependency parsing, the GloVe model of word vectors, neural machine translation, question answering, and deep language understanding.
OnLive shows one strategy, moving to the cloud while preserving the document-centric model of Word, Excel, Powerpoint, and, tellingly, Gmail instead of Outlook.
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The cognitive models of word production involve several processing levels.
Erk, K. Vector space models of word meaning and phrase meaning: a survey.
We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition.
These results are discussed in relation to current models of word spelling.
Consequences for the architecture of the early lexicon and for models of word learning are discussed.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com