Amir Dezfouli

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Bernard BalleineUNSW SydneyVerified email at unsw.edu.au
Mehdi KeramatiMaxPlanck Centre for Computational Psychiatry, UCLVerified email at gatsby.ucl.ac.uk
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Verified email at data61.csiro.au
Payam PirayAssistant Professor of Psychology and Neuroscience at USCVerified email at usc.edu
Richard NockGoogle ResearchVerified email at uniagro.fr
Kristi R. GriffithsSenior Research Fellow, InsideOut InstituteVerified email at sydney.edu.au
Richard W MorrisTranslational datascientist, University of SydneyVerified email at sydney.edu.au
iadine ChadèsPrincipal Research Scientist CSIROVerified email at csiro.au
Nura LingawiResearch associate, UNSW SydneyVerified email at unsw.edu.au
Hamed Ekhtiari, MD, PhD,Laureate Institute for Brain ResearchVerified email at laureateinstitute.org
Fabio RamosUniversity of Sydney and NVIDIAVerified email at sydney.edu.au
Christian WalderGoogle DeepMindVerified email at google.com
Michael NorrishAustralian National UniversityVerified email at anu.edu.au
Mieke van HolsteinPostdoctoral research fellowVerified email at ubc.ca
Laura BradfieldCentre for Neuroscience and Regenerative Medicine, University of Technology, SydneyVerified email at uts.edu.au
Tom BlauResearch Scientist, CSIROVerified email at sydney.edu.au
Tom HeskesProfessor of Computer Science and Artificial Intelligence, Radboud University NijmegenVerified email at science.ru.nl
Nathaniel D. DawHuo Professor of Computational and Theoretical Neuroscience, Princeton UniversityVerified email at princeton.edu
Michael J FrankProfessor, Director Center for Computational Brain Science, Brown UniversityVerified email at brown.edu
Minchao WuAustralian National UniversityVerified email at anu.edu.au

Amir Dezfouli

BIMLOGIQ

Verified email at bimlogiq.com - Homepage

Computational neuroscience Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Speed/accuracy trade-off between the habitual and the goal-directed processes M Keramati, A Dezfouli, P Piray PLoS computational biology 7 (5), e1002055, 2011	476	2011
Habits, action sequences and reinforcement learning A Dezfouli, BW Balleine European Journal of Neuroscience 35 (7), 1036-1051, 2012	407	2012
Actions, action sequences and habits: evidence that goal-directed and habitual action control are hierarchically organized A Dezfouli, BW Balleine PLoS computational biology 9 (12), e1003364, 2013	303	2013
Medial Orbitofrontal Cortex Mediates Outcome Retrieval in Partially Observable Task Situations LA Bradfield, A Dezfouli, M van Holstein, B Chieng, BW Balleine Neuron 88 (6), 1268–1280, 2015	213	2015
Habits as action sequences: hierarchical action control and changes in outcome value A Dezfouli, NW Lingawi, BW Balleine Philosophical Transactions of the Royal Society B: Biological Sciences 369 …, 2014	178	2014
Hierarchical Bayesian inference for concurrent model fitting and comparison for group studies P Piray, A Dezfouli, T Heskes, MJ Frank, ND Daw PLoS computational biology 15 (6), e1007043, 2019	112	2019
Hierarchical action control: Adaptive collaboration between actions and habits. BW Balleine, A Dezfouli Frontiers in Psychology 10, 2735, 2019	81	2019
Scalable Inference for Gaussian Process Models with Black-Box Likelihoods A Dezfouli, E Bonilla Advances in Neural Information Processing Systems (NIPS), 2015	68	2015
Models that learn how humans learn: The case of decision-making and its disorders A Dezfouli, K Griffiths, F Ramos, P Dayan, BW Balleine PLoS computational biology 15 (6), e1006903, 2019	67	2019
Action-value comparisons in the dorsolateral prefrontal cortex control choice between goal-directed actions RW Morris, A Dezfouli, KR Griffiths, BW Balleine Nature communications 5, 2014	63	2014
A neurocomputational model for cocaine addiction A Dezfouli, P Piray, MM Keramati, H Ekhtiari, C Lucas, A Mokri Neural computation 21 (10), 2869-2893, 2009	62	2009
Hierarchical control of goal-directed action in the cortical–basal ganglia network BW Balleine, A Dezfouli, M Ito, K Doya Current opinion in behavioral sciences 5, 1-7, 2015	61	2015
Adversarial vulnerabilities of human decision-making A Dezfouli, R Nock, P Dayan Proceedings of the National Academy of Sciences 117 (46), 29221-29228, 2020	51	2020
Optimizing sequential experimental design with deep reinforcement learning T Blau, EV Bonilla, I Chades, A Dezfouli International conference on machine learning, 2107-2128, 2022	49	2022
Individual differences in nucleus accumbens dopamine receptors predict development of addiction-like behavior: a computational approach P Piray, MM Keramati, A Dezfouli, C Lucas, A Mokri Neural computation 22 (9), 2334-2368, 2010	48	2010
Tacticzero: Learning to prove theorems from scratch with deep reinforcement learning M Wu, M Norrish, C Walder, A Dezfouli Advances in Neural Information Processing Systems 34, 9330-9342, 2021	44	2021
Disentangled behavioural representations A Dezfouli, H Ashtiani, O Ghattas, R Nock, P Dayan, CS Ong Advances in neural information processing systems 32, 2019	37	2019
Optimizing the depth and the direction of prospective planning using information values CE Sezener, A Dezfouli, M Keramati PLoS computational biology 15 (3), e1006827, 2019	34	2019
The psychological and physiological mechanisms of habit formation NW Lingawi, A Dezfouli, BW Balleine The Wiley handbook on the cognitive neuroscience of learning, 409-441, 2016	33	2016
Integrated accounts of behavioral and neuroimaging data using flexible recurrent neural network models A Dezfouli, R Morris, FT Ramos, P Dayan, B Balleine Advances in neural information processing systems 31, 2018	25	2018

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