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Alexandre L S Filipowicz

Biographic Data

ID1843514
NAMEAlexandre L S Filipowicz
GIVEN NAMESAlexandre L S
FAMILY NAMEFilipowicz
SIGNATUREFILIPOWICZ A L S
AFFILIATIONSUniversity of Pennsylvania
ORCID0000-0002-1311-386X
VERIFIEDNo
TOTAL WORKS2
TOTAL CITATIONS2
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2018
LATEST PUBLICATION YEAR2024
H-INDEX1
  • Plinko

    Open Access•Peter A V DiBerardino, Alexandre L S Filipowicz et al.•ARTICLE•British Journal of Psychology•2024•References: 80

    Prior beliefs are central to Bayesian accounts of cognition, but many of these accounts do not directly measure priors. More specifically, initial states of belief heavily influence how new information is assumed to be utilized when updating a particular model. Despite this, prior and posterior beliefs are either inferred from sequential participant actions or elicited through impoverished means. We had participants to play a version of the game …

  • A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment

    Open Access•Christopher M Glaze, Alexandre L S Filipowicz et al.•ARTICLE•Nature Human Behaviour•2018•Cited by: 2•References: 57

  • A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment

    Open Access•Christopher M Glaze, Alexandre L S Filipowicz et al.•ARTICLE•Nature Human Behaviour•2018•Cited by: 2•References: 57

  • A bias–variance trade-off governs individual differences in on-line learning in an unpredictable environment

    Open Access•Christopher M Glaze, Alexandre L S Filipowicz et al.•ARTICLE•Nature Human Behaviour•2018•Cited by: 2•References: 57

  • Plinko

    Open Access•Peter A V DiBerardino, Alexandre L S Filipowicz et al.•ARTICLE•British Journal of Psychology•2024•References: 80

    Prior beliefs are central to Bayesian accounts of cognition, but many of these accounts do not directly measure priors. More specifically, initial states of belief heavily influence how new information is assumed to be utilized when updating a particular model. Despite this, prior and posterior beliefs are either inferred from sequential participant actions or elicited through impoverished means. We had participants to play a version of the game …

Artificial Intelligence (2 works) · Computer Science (2 works) · Machine learning (2 works) · Artificial Intelligence (1 work) · Bayesian inference (1 work) · Bayesian Modeling and Causal Inference (1 work) · Bayesian probability (1 work) · Bottleneck (1 work) · Child and Animal Learning Development (1 work) · Cognition (1 work)

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