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2020 – today
- 2022
[c21]Mamady Nabé, Jean-Luc Schwartz, Julien Diard:
Bayesian gates: a probabilistic modeling tool for temporal segmentation of sensory streams into sequences of perceptual accumulators. CogSci 2022- [c20]Alexandra Steinhilber, Sylviane Valdois, Julien Diard:
Bayesian comparators: a probabilistic modeling tool for similarity evaluation between predicted and perceived patterns. CogSci 2022 - [c19]Marc-Antoine Georges, Julien Diard, Laurent Girin, Jean-Luc Schwartz, Thomas Hueber:
Repeat after Me: Self-Supervised Learning of Acoustic-to-Articulatory Mapping by Vocal Imitation. ICASSP 2022: 8252-8256 - [c18]Mamady Nabé
, Julien Diard, Jean-Luc Schwartz:
Isochronous is beautiful? Syllabic event detection in a neuro-inspired oscillatory model is facilitated by isochrony in speech. INTERSPEECH 2022: 4671-4675 - [i2]Marc-Antoine Georges, Julien Diard, Laurent Girin, Jean-Luc Schwartz, Thomas Hueber:
Repeat after me: Self-supervised learning of acoustic-to-articulatory mapping by vocal imitation. CoRR abs/2204.02269 (2022) - 2021
- [j9]Laurent Girin, Simon Leglaive, Xiaoyu Bie, Julien Diard, Thomas Hueber, Xavier Alameda-Pineda:
Dynamical Variational Autoencoders: A Comprehensive Review. Found. Trends Mach. Learn. 15(1-2): 1-175 (2021) - 2020
- [c17]Ali Saghiran, Sylviane Valdois, Julien Diard:
Simulating length and frequency effects across multiple tasks with the Bayesian model BRAID-Phon. CogSci 2020 - [i1]Laurent Girin, Simon Leglaive, Xiaoyu Bie, Julien Diard, Thomas Hueber, Xavier Alameda-Pineda:
Dynamical Variational Autoencoders: A Comprehensive Review. CoRR abs/2008.12595 (2020)
2010 – 2019
- 2018
- [j8]Jean-François Patri, Pascal Perrier, Jean-Luc Schwartz, Julien Diard:
What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework. PLoS Comput. Biol. 14(1) (2018) - [c16]Thierry Phenix, Sylviane Valdois, Julien Diard:
Reconciling opposite neighborhood frequency effects in lexical decision: Evidence from a novel probabilistic model of visual word recognition. CogSci 2018 - [c15]Marie-Lou Barnaud, Julien Diard, Pierre Bessière, Jean-Luc Schwartz:
COSMO SylPhon: A Bayesian Perceptuo-motor Model to Assess Phonological Learning. INTERSPEECH 2018: 3786-3790 - 2017
- [j7]Sylvain Harquel, Julien Diard, Estelle Raffin, Brice Passera, Gaelle Dall'Igna, Christian Marendaz, Olivier David, Alan Chauvin:
Automatized set-up procedure for transcranial magnetic stimulation protocols. NeuroImage 153: 307-318 (2017) - 2016
- [c14]Marie-Lou Barnaud, Jean-Luc Schwartz, Julien Diard, Pierre Bessière:
Sensorimotor learning in a Bayesian computational model of speech communication. ICDL-EPIROB 2016: 27-32 - [c13]Marie-Lou Barnaud, Julien Diard, Pierre Bessière, Jean-Luc Schwartz:
Assessing Idiosyncrasies in a Bayesian Model of Speech Communication. INTERSPEECH 2016: 2080-2084 - [c12]Jean-François Patri, Pascal Perrier, Julien Diard:
Bayesian Modeling in Speech Motor Control: A Principled Structure for the Integration of Various Constraints. INTERSPEECH 2016: 3588-3592 - [c11]Jean-François Patri, Julien Diard, Pascal Perrier:
Modélisation bayésienne de la planification motrice des gestes de parole: Évaluation du rôle des différentes modalités sensorielles (Bayesian modeling of speech gesture motor planning: Evaluating the role of different sensory modalities ). JEP-TALN-RECITAL (1) 2016: 419-427 - 2015
- [j6]Jean-François Patri, Julien Diard, Pascal Perrier:
Optimal speech motor control and token-to-token variability: a Bayesian modeling approach. Biol. Cybern. 109(6): 611-626 (2015) - [j5]Clément Moulin-Frier, Julien Diard, Jean-Luc Schwartz, Pierre Bessière:
COSMO ("Communicating about Objects using Sensory-Motor Operations"): A Bayesian modeling framework for studying speech communication and the emergence of phonological systems. J. Phonetics 53: 5-41 (2015) - [c10]Marie-Lou Barnaud, Julien Diard, Pierre Bessière, Jean-Luc Schwartz:
COSMO, a Bayesian computational model of speech communication: Assessing the role of sensory vs. motor knowledge in speech perception. ICDL-EPIROB 2015: 248-249 - 2014
- [c9]Myriam Chanceaux, Vincent Rynik, Jean Lorenceau, Julien Diard:
Writer recognition in cursive eye writing: A Bayesian model. CogSci 2014 - 2013
- [j4]Julien Diard, Pierre Bessière, Alain Berthoz:
Spatial Memory of Paths Using Circular Probability Distributions: Theoretical Properties, Navigation Strategies and Orientation Cue Combination. Spatial Cogn. Comput. 13(3): 219-257 (2013) - [c8]Raphaël Laurent, Jean-Luc Schwartz, Pierre Bessière, Julien Diard:
A computational model of perceptuo-motor processing in speech perception: learning to imitate and categorize synthetic CV syllables. INTERSPEECH 2013: 2797-2801 - 2012
- [c7]Raphaël Laurent, Jean-Luc Schwartz, Pierre Bessière, Julien Diard:
COSMO, un modèle bayésien de la communication parlée : application à la perception des syllabes (COSMO, a Bayesian model of speech communication, applied to syllable perception) [in French]. JEP-TALN-RECITAL 2012 2012: 305-312 - 2010
- [j3]Julien Diard, Estelle Gilet, Éva Simonin, Pierre Bessière:
Incremental learning of Bayesian sensorimotor models: from low-level behaviours to large-scale structure of the environment. Connect. Sci. 22(4): 291-312 (2010)
2000 – 2009
- 2008
- [c6]Éva Simonin, Julien Diard:
BBPRM: A behavior-based probabilistic roadmap method. SMC 2008: 1719-1724 - [p1]Julien Diard, Pierre Bessière:
Bayesian Maps: Probabilistic and Hierarchical Models for Mobile Robot Navigation. Probabilistic Reasoning and Decision Making in Sensory-Motor Systems 2008: 153-175 - 2005
- [c5]Éva Simonin, Julien Diard, Pierre Bessière:
Learning Bayesian models of sensorimotor interaction: from random exploration toward the discovery of new behaviors. IROS 2005: 1307-1312 - [c4]Julien Diard, Pierre Bessière, Emmanuel Mazer:
Merging probabilistic models of navigation: the Bayesian map and the superposition operator. IROS 2005: 1326-1331 - 2004
- [j2]Olivier Lebeltel, Pierre Bessière, Julien Diard, Emmanuel Mazer:
Bayesian Robot Programming. Auton. Robots 16(1): 49-79 (2004) - [j1]Olivier Lebeltel, Pierre Bessière, Julien Diard, Emmanuel Mazer:
Programmation bayésienne des robots. Rev. d'Intelligence Artif. 18(2): 261-298 (2004) - [c3]Julien Diard, Pierre Bessière, Emmanuel Mazer:
A Theoretical Comparison of Probabilistic and Biomimetic Models of Mobile Robot Navigation. ICRA 2004: 933-938 - [c2]Julien Diard, Pierre Bessière, Emmanuel Mazer:
Hierarchies of Probabilistic Models of Navigation: the Bayesian Map and the Abstraction Operator. ICRA 2004: 3837-3842 - 2003
- [b1]Julien Diard:
La carte bayésienne : un modèle probabiliste hiérarchique pour la navigation en robotique mobile. (The Bayesian map - A hierarchical probabilistic model for mobile robot navigation). Grenoble Institute of Technology, France, 2003 - [c1]David Bellot, Roland Siegwart, Pierre Bessière, Adriana Tapus, Christophe Coué, Julien Diard:
Bayesian Modeling and Reasoning for Real World Robotics: Basics and Examples. Embodied Artificial Intelligence 2003: 186-201
Coauthor Index
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