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Ulrik Beierholm

Biographic Data

ID9667070
NAMEUlrik Beierholm
GIVEN NAMESUlrik
FAMILY NAMEBeierholm
SIGNATUREBEIERHOLM U
AFFILIATIONSDurham University
ORCID0000-0002-7296-7996
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS0
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2020
LATEST PUBLICATION YEAR2026
H-INDEX0
  • Crossmodal interaction of flashes and beeps across time and number follows Bayesian causal inference

    Open Access•Haocheng Zhu, Yiyang Zhang et al.•ARTICLE•Psychonomic Bulletin & Review•2026

    Multisensory perception requires the brain to dynamically infer causal relationships between sensory inputs across various dimensions, such as temporal and spatial attributes. Traditionally, Bayesian Causal Inference (BCI) models have generally provided a robust framework for understanding sensory processing in unidimensional settings where stimuli across sensory modalities vary along one dimension such as spatial location, or numerosity (Samad e…

  • Using Occam’s razor and Bayesian modelling to compare discrete and continuous representations in numerosity judgements

    Open Access•Jake Spicer, Adam N Sanborn et al.•ARTICLE•Cognitive Psychology•2020

No prominent works on this page.

  • Using Occam’s razor and Bayesian modelling to compare discrete and continuous representations in numerosity judgements

    Open Access•Jake Spicer, Adam N Sanborn et al.•ARTICLE•Cognitive Psychology•2020

  • Crossmodal interaction of flashes and beeps across time and number follows Bayesian causal inference

    Open Access•Haocheng Zhu, Yiyang Zhang et al.•ARTICLE•Psychonomic Bulletin & Review•2026

    Multisensory perception requires the brain to dynamically infer causal relationships between sensory inputs across various dimensions, such as temporal and spatial attributes. Traditionally, Bayesian Causal Inference (BCI) models have generally provided a robust framework for understanding sensory processing in unidimensional settings where stimuli across sensory modalities vary along one dimension such as spatial location, or numerosity (Samad e…

Bayesian probability (2 works) · Artificial Intelligence (1 work) · Artificial Intelligence (1 work) · Bayesian inference (1 work) · Cognitive psychology (1 work) · Computer Science (1 work) · Crossmodal (1 work) · Econometrics (1 work) · Illusion (1 work) · Mathematics (1 work)

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