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Jakub Szymanik

Showing results (1-10 of 21) with videos related to

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Neuropsychologia|March 6, 2007
A comment on a neuroimaging study of natural language quantifier comprehensionJakub Szymanik
Cognitive Science|July 13, 2022
Heavy Tails and the Shape of Modified NumeralsFausto Carcassi, Jakub Szymanik
Neuropsychologia|July 18, 2009
Improving methodology of quantifier comprehension experimentsJakub Szymanik, Marcin Zajenkowski
Cognitive Science|May 14, 2011
Comprehension of simple quantifiers: empirical evaluation of a computational modelJakub Szymanik, Marcin Zajenkowski
Cognition|July 20, 2023
The Boolean Language of Thought is recoverable from learning dataFausto Carcassi, Jakub Szymanik
Open Mind : Discoveries in Cognitive Science|November 28, 2022
Neural Networks Track the Logical Complexity of Boolean ConceptsFausto Carcassi, Jakub Szymanik
Cognitive Science|March 18, 2024
Recursive Numeral Systems Optimize the Trade-off Between Lexicon Size and Average Morphosyntactic ComplexityMilica Denić, Jakub Szymanik
Cognition|November 23, 2019
Ease of learning explains semantic universalsShane Steinert-Threlkeld, Jakub Szymanik
Journal of Communication Disorders|September 2, 2011
A computational approach to quantifiers as an explanation for some language impairments in schizophreniaMarcin Zajenkowski, Rafał Styła, Jakub Szymanik
Journal of Psycholinguistic Research|December 31, 2013
Working memory mechanism in proportional quantifier verificationMarcin Zajenkowski, Jakub Szymanik, Maria Garraffa
Pageof 3

Showing results (1-10 of 21) with videos related to

Sort By:
Pageof 3
Neuropsychologia|March 6, 2007
A comment on a neuroimaging study of natural language quantifier comprehensionJakub Szymanik
Cognitive Science|July 13, 2022
Heavy Tails and the Shape of Modified NumeralsFausto Carcassi, Jakub Szymanik
Neuropsychologia|July 18, 2009
Improving methodology of quantifier comprehension experimentsJakub Szymanik, Marcin Zajenkowski
Cognitive Science|May 14, 2011
Comprehension of simple quantifiers: empirical evaluation of a computational modelJakub Szymanik, Marcin Zajenkowski
Cognition|July 20, 2023
The Boolean Language of Thought is recoverable from learning dataFausto Carcassi, Jakub Szymanik
Open Mind : Discoveries in Cognitive Science|November 28, 2022
Neural Networks Track the Logical Complexity of Boolean ConceptsFausto Carcassi, Jakub Szymanik
Cognitive Science|March 18, 2024
Recursive Numeral Systems Optimize the Trade-off Between Lexicon Size and Average Morphosyntactic ComplexityMilica Denić, Jakub Szymanik
Cognition|November 23, 2019
Ease of learning explains semantic universalsShane Steinert-Threlkeld, Jakub Szymanik
Journal of Communication Disorders|September 2, 2011
A computational approach to quantifiers as an explanation for some language impairments in schizophreniaMarcin Zajenkowski, Rafał Styła, Jakub Szymanik
Journal of Psycholinguistic Research|December 31, 2013
Working memory mechanism in proportional quantifier verificationMarcin Zajenkowski, Jakub Szymanik, Maria Garraffa
Pageof 3