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Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Pattern Recognition and Machine Learning
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Category-like representation of statistical regularities allows for stable distractor suppression
inferred← citeshttps://doi.org/10.3389/fpsyt.2025.1581802openalex-snapshot
Cognitive effort devaluation and the salience network: a computational model of amotivation in depression
inferred← citeshttps://doi.org/10.3724/sp.j.1042.2021.00677openalex-snapshot
The computational and neural substrates underlying social learning
inferred← citeshttps://doi.org/10.3758/s13415-023-01137-wopenalex-snapshot
A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals
inferred← citeshttps://doi.org/10.3758/s13428-025-02599-1openalex-snapshot
Sample size matters when estimating test–retest reliability of behaviour
inferred← citeshttps://doi.org/10.3788/gzxb20255409.0954201openalex-snapshot
“AI+光学”交叉学科体系的内涵与架构研究（特邀）
inferred← citeshttps://doi.org/10.48550/arxiv.1901.01916openalex-snapshot
Bayesian inference over model-spaces increases the accuracy of model comparison and allows formal testing of hypotheses about model distributions in experimental populations
inferred← citeshttps://doi.org/10.64898/2025.12.24.696333openalex-snapshot
Dopamine drives a positive reward bias on human reinforcement learning
inferred← citeshttps://doi.org/10.64898/2026.02.11.705395openalex-snapshot
Efficient Learning of Predictive Maps for Flexible Planning
inferred← citeshttps://doi.org/10.64898/2026.05.14.725268openalex-snapshot
Categorical Bayes Filtering for Computational Phenotyping in Adaptive Learning
inferred← citeshttps://doi.org/10.64898/2026.06.02.729586openalex-snapshot
Flexible route planning and rapid structure learning by mice in complex environments
inferred← citeshttps://doi.org/10.64898/2026.06.05.730398openalex-snapshot
HSSM: A Widely Applicable Toolbox for Hierarchical Bayesian Neurocognitive Modeling
inferred← citeshttps://doi.org/10.7324/japs.2021.110705openalex-snapshot
Hierarchical Bayesian approach applied to the formulation of sustained-release suppositories and dissolution profile modeling
inferred← citeshttps://doi.org/10.7554/elife.104008openalex-snapshot
Self-other generalisation shapes social interaction and is disrupted in borderline personality disorder
inferred← citeshttps://doi.org/10.7554/elife.104008.1openalex-snapshot
Self-other generalisation shapes social interaction and is disrupted in borderline personality disorder
inferred← citeshttps://doi.org/10.7554/elife.104008.2openalex-snapshot
Self-Other Generalisation Shapes Social Interaction and Is Disrupted in Borderline Personality Disorder
inferred← citeshttps://doi.org/10.7554/elife.104008.3openalex-snapshot
Self-Other Generalisation Shapes Social Interaction and Is Disrupted in Borderline Personality Disorder
inferred← citeshttps://doi.org/10.7554/elife.104008.4openalex-snapshot
Self-other generalisation shapes social interaction and is disrupted in borderline personality disorder
inferred← citeshttps://doi.org/10.7554/elife.109185openalex-snapshot
Impaired Adaptive Learning in Chronic Pain Contributes to Apathy
inferred← citeshttps://doi.org/10.7554/elife.109185.1openalex-snapshot
Impaired Adaptive Learning in Chronic Pain Contributes to Apathy
inferred← citeshttps://doi.org/10.7554/elife.49058openalex-snapshot
Modeling the dynamics of Plasmodium falciparum gametocytes in humans during malaria infection
inferred← citeshttps://doi.org/10.7554/elife.49547openalex-snapshot
Ten simple rules for the computational modeling of behavioral data
inferred← citeshttps://doi.org/10.7554/elife.66169openalex-snapshot
Computational modeling of threat learning reveals links with anxiety and neuroanatomy in humans
inferred← citeshttps://doi.org/10.7554/elife.68943openalex-snapshot
Value signals guide abstraction during learning
inferred← citeshttps://doi.org/10.7554/elife.84260openalex-snapshot
Novelty and uncertainty differentially drive exploration across development
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