Julien Diard
Julien Diard
Laboratoire de Psychologie et NeuroCognition - CNRS
Verified email at - Homepage
Cited by
Cited by
Bayesian robot programming
O Lebeltel, P Bessiere, J Diard, E Mazer
Autonomous Robots 16 (1), 49-79, 2004
Dynamical variational autoencoders: A comprehensive review
L Girin, S Leglaive, X Bie, J Diard, T Hueber, X Alameda-Pineda
Foundations and Trends in Machine Learning 15 (1-2), 1-175, 2020
Common Bayesian models for common cognitive issues
F Colas, J Diard, P Bessiere
Acta biotheoretica 58, 191-216, 2010
Adverse conditions improve distinguishability of auditory, motor, and perceptuo-motor theories of speech perception: An exploratory Bayesian modelling study
C Moulin-Frier, R Laurent, P Bessière, JL Schwartz, J Diard
Speech Recognition in Adverse Conditions, 288-311, 2013
Enhancing reading performance through action video games: The role of visual attention span
A Antzaka, M Lallier, S Meyer, J Diard, M Carreiras, S Valdois
Scientific reports 7 (1), 14563, 2017
COSMO (“Communicating about Objects using Sensory–Motor Operations”): A Bayesian modeling framework for studying speech communication and the emergence of phonological systems
C Moulin-Frier, J Diard, JL Schwartz, P Bessière
Journal of Phonetics 53, 5-41, 2015
Bayesian action–perception computational model: Interaction of production and recognition of cursive letters
E Gilet, J Diard, P Bessiere
PloS one 6 (6), e20387, 2011
Optimal speech motor control and token-to-token variability: a Bayesian modeling approach
JF Patri, J Diard, P Perrier
Biological cybernetics 109, 611-626, 2015
Modeling the length effect for words in lexical decision: The role of visual attention
E Ginestet, T Phénix, J Diard, S Valdois
Vision research 159, 10-20, 2019
The complementary roles of auditory and motor information evaluated in a Bayesian perceptuo-motor model of speech perception.
R Laurent, ML Barnaud, JL Schwartz, P Bessière, J Diard
Psychological review 124 (5), 572, 2017
What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework
JF Patri, P Perrier, JL Schwartz, J Diard
PLoS computational biology 14 (1), e1005942, 2018
La carte bayésienne: un modèle probabiliste hiérarchique pour la navigation en robotique mobile
J Diard
Institut National Polytechnique de Grenoble-INPG, 2003
Automatized set-up procedure for transcranial magnetic stimulation protocols
S Harquel, J Diard, E Raffin, B Passera, G Dall'Igna, C Marendaz, O David, ...
Neuroimage 153, 307-318, 2017
Reanalyzing neurocognitive data on the role of the motor system in speech perception within COSMO, a Bayesian perceptuo-motor model of speech communication
ML Barnaud, P Bessière, J Diard, JL Schwartz
Brain and language 187, 19-32, 2018
Les modèles computationnels de lecture
T Phénix, J Diard, S Valdois
Traité de neurolinguistique, 167-182, 2016
Proxemics models for human-aware navigation in robotics: Grounding interaction and personal space models in experimental data from psychology
ML Barnaud, N Morgado, R Palluel-Germain, J Diard, A Spalanzani
Proceedings of the 3rd IROS’2014 workshop “Assistance and Service Robotics …, 2014
Computer simulations of coupled idiosyncrasies in speech perception and speech production with COSMO, a perceptuo-motor Bayesian model of speech communication
ML Barnaud, JL Schwartz, P Bessière, J Diard
PloS one 14 (1), e0210302, 2019
Probabilistic modeling of orthographic learning based on visuo-attentional dynamics
E Ginestet, S Valdois, J Diard
Psychonomic Bulletin & Review 29 (5), 1649-1672, 2022
Modeling sensory preference in speech motor planning: a Bayesian modeling framework
JF Patri, J Diard, P Perrier
Frontiers in Psychology 10, 469247, 2019
Bayesian programming and hierarchical learning in robotics
J Diard, O Lebeltel
SAB2000 Proceedings Supplement Book, 10pages, 2000
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