Publications#
Our most recent publications:
2025
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An introduction to Sequential Monte Carlo for Bayesian inference and model comparison—with examples for psychology and behavioral science
Max Hinne
Behavior Research Methods 57 (5), 125, 2025
2024
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Non-Gaussian normative modelling with hierarchical Bayesian regression
Augustijn AA de Boer et al.
Imaging Neuroscience 2, 1-36, 2024 -
Individual differences in processing speed and curiosity explain infant habituation and dishabituation performance
Francesco Poli, Tommaso Ghilardi, Roseriet Beijers, Carolina de Weerth, Max Hinne, Rogier B Mars and Sabine Hunnius
Developmental Science 27 (3), e13460, 2024 -
Robust inference of dynamic covariance using Wishart processes and sequential Monte Carlo
Hester Huijsdens, David Leeftink, Linda Geerligs and Max Hinne
Entropy 26 (8), 695, 2024
2023
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PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework
Alexander JM Dingemans et al.
Nature Genetics 55 (9), 1598-1607, 2023 -
Clustering children's learning behaviour to identify self-regulated learning support needs
SHE Dijkstra, Max Hinne, Eliane Segers and Inge Molenaar
Computers in Human Behavior 145, 107754, 2023 -
Eight-month-old infants meta-learn by downweighting irrelevant evidence
Francesco Poli, Tommaso Ghilardi, Rogier B Mars, Max Hinne and Sabine Hunnius
Open Mind 7, 141-155, 2023
2022
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DeNovoCNN: a deep learning approach to de novo variant calling in next generation sequencing data
Gelana Khazeeva et al.
Nucleic Acids Research, 2022 -
Phenotype based prediction of exome sequencing outcome using machine learning for neurodevelopmental disorders
Alexander JM Dingemans et al.
Genetics in Medicine 24 (3), 645-653, 2022 -
Bayesian model averaging for nonparametric discontinuity design
Max Hinne, David Leeftink, Marcel AJ van Gerven and Luca Ambrogioni
Plos one 17 (6), e0270310, 2022
2021
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The JASP guidelines for conducting and reporting a Bayesian analysis
Johnny Van Doorn et al.
Psychonomic Bulletin & Review 28, 813-826, 2021 -
Automatic structured variational inference
Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore and Marcel van Gerven
International Conference on Artificial Intelligence and Statistics, 676-684, 2021 -
Real time measuring of individual learners' self regulation during learning
SHE Dijkstra, I Molenaar and M Hinne
[Sl]: European Association for Research on Learning and Instruction (EARLI), 2021
2020
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A conceptual introduction to Bayesian model averaging
Max Hinne, Quentin F Gronau, Don van den Bergh and Eric-Jan Wagenmakers
Advances in Methods and Practices in Psychological Science 3 (2), 200-215, 2020 -
A tutorial on conducting and interpreting a Bayesian ANOVA in JASP
Don van den Bergh et al.
L’Année psychologique 120 (1), 73-96, 2020 -
The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test
Alexander Ly et al.
Computational Brain & Behavior 3, 153-161, 2020 -
Validation of structural brain connectivity networks: The impact of scanning parameters
Karen S Ambrosen et al.
Neuroimage 204, 116207, 2020 -
Highways to happiness for autistic adults? Perceived causal relations among clinicians
Marie K Deserno, Denny Borsboom, Sander Begeer, Riet van Bork, Max Hinne and Hilde M Geurts
Plos one 15 (12), e0243298, 2020 -
Spectral discontinuity design: Interrupted time series with spectral mixture kernels
David Leeftink and Max Hinne
Machine Learning for Health, 213-225, 2020 -
The Indian chefs process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel Gerven and François Laviolette
Conference on Uncertainty in Artificial Intelligence, 600-608, 2020 -
Tutorial para realizar e interpretar un análisis de la varianza bayesiana en JASP
Don van den Bergh et al.
L’Année psychologique 120 (1), 73-96, 2020
2019
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Node centrality measures are a poor substitute for causal inference
Fabian Dablander and Max Hinne
Scientific reports 9 (1), 6846, 2019 -
Between-subject variability in the influence of mental imagery on conscious perception
Nadine Dijkstra, Max Hinne, Sander Erik Bosch and MAJ Van Gerven
Scientific reports 9 (1), 15658, 2019 -
Forward amortized inference for likelihood-free variational marginalization
Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva Borne, Yaǧmur Güçlütürk, Max Hinne, Eric Maris and Marcel Gerven
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 -
SpikeCaKe: Semi-analytic nonparametric Bayesian inference for spike-spike neuronal connectivity
Luca Ambrogioni, Patrick Ebel, Max Hinne, Umut Güçlü, Marcel Gerven and Eric Maris
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 -
Visual imagery strength and sensory ambiguity
N Dijkstra, M Hinne, SE Bosch and MAJ van Gerven
Radboud Data Repository, 2019