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Max Hinne

Showing results (1-10 of 22) with videos related to

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Behavior Research Methods|March 26, 2025
An introduction to Sequential Monte Carlo for Bayesian inference and model comparison-with examples for psychology and behavioral scienceMax Hinne
Scientific Reports|May 4, 2019
Node centrality measures are a poor substitute for causal inferenceFabian Dablander, Max Hinne
Entropy (Basel, Switzerland)|August 29, 2024
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte CarloHester Huijsdens, David Leeftink, Linda Geerligs, et al.
Open Mind : Discoveries in Cognitive Science|July 7, 2023
Eight-Month-Old Infants Meta-Learn by Downweighting Irrelevant EvidenceFrancesco Poli, Tommaso Ghilardi, Rogier B Mars, et al.
Plos One|June 30, 2022
Bayesian model averaging for nonparametric discontinuity designMax Hinne, David Leeftink, Marcel A J van Gerven, et al.
Frontiers in Computational Neuroscience|October 24, 2014
Quantifying uncertainty in brain network measures using Bayesian connectomicsRonald J Janssen, Max Hinne, Tom Heskes, et al.
Plos Computational Biology|November 6, 2015
Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity EstimatesMax Hinne, Ronald J Janssen, Tom Heskes, et al.
Neuroimage|October 9, 2012
Bayesian inference of structural brain networksMax Hinne, Tom Heskes, Christian F Beckmann, et al.
Neuroimage|October 15, 2013
Structurally-informed Bayesian functional connectivity analysisMax Hinne, Luca Ambrogioni, Ronald J Janssen, et al.
Plos One|January 31, 2015
Probabilistic clustering of the human connectome identifies communities and hubsMax Hinne, Matthias Ekman, Ronald J Janssen, et al.
Pageof 3

Showing results (1-10 of 22) with videos related to

Sort By:
Pageof 3
Behavior Research Methods|March 26, 2025
An introduction to Sequential Monte Carlo for Bayesian inference and model comparison-with examples for psychology and behavioral scienceMax Hinne
Scientific Reports|May 4, 2019
Node centrality measures are a poor substitute for causal inferenceFabian Dablander, Max Hinne
Entropy (Basel, Switzerland)|August 29, 2024
Robust Inference of Dynamic Covariance Using Wishart Processes and Sequential Monte CarloHester Huijsdens, David Leeftink, Linda Geerligs, et al.
Open Mind : Discoveries in Cognitive Science|July 7, 2023
Eight-Month-Old Infants Meta-Learn by Downweighting Irrelevant EvidenceFrancesco Poli, Tommaso Ghilardi, Rogier B Mars, et al.
Plos One|June 30, 2022
Bayesian model averaging for nonparametric discontinuity designMax Hinne, David Leeftink, Marcel A J van Gerven, et al.
Frontiers in Computational Neuroscience|October 24, 2014
Quantifying uncertainty in brain network measures using Bayesian connectomicsRonald J Janssen, Max Hinne, Tom Heskes, et al.
Plos Computational Biology|November 6, 2015
Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity EstimatesMax Hinne, Ronald J Janssen, Tom Heskes, et al.
Neuroimage|October 9, 2012
Bayesian inference of structural brain networksMax Hinne, Tom Heskes, Christian F Beckmann, et al.
Neuroimage|October 15, 2013
Structurally-informed Bayesian functional connectivity analysisMax Hinne, Luca Ambrogioni, Ronald J Janssen, et al.
Plos One|January 31, 2015
Probabilistic clustering of the human connectome identifies communities and hubsMax Hinne, Matthias Ekman, Ronald J Janssen, et al.
Pageof 3