Francois Rivest

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Thomas ShultzProfessor of Psychology, McGill UniversityVerified email at mcgill.ca
JP ThiviergeFull professor of Psychology, University of OttawaVerified email at uottawa.ca
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Elliot A. LudvigProfessor, Psychology, University of WarwickVerified email at warwick.ac.uk
John F. KalaskaUniversité de MontréalVerified email at umontreal.ca
André LuzardoAssistant Professor, Universidad Francisco de VitoriaVerified email at ufv.es
Doina PrecupDeepMind and McGill UniversityVerified email at cs.mcgill.ca
Fuat BalcıProfessor of Biological Sciences, University of ManitobaVerified email at umanitoba.ca
Peter Killeenx-Professor of Psychology, Arizona State UniversityVerified email at asu.edu
Patrick SimenAssociate Professor of Neuroscience, Oberlin CollegeVerified email at oberlin.edu
Farhana ZulkernineAssociate Professor, School of Computing, Queen's UniversityVerified email at queensu.ca
Ali EtemadQueen's UniversityVerified email at queensu.ca
Oury MonchiCentre de recherche de l'institut universitaire de gériatrie de Montréal, Université de MontréalVerified email at umontreal.ca
Jean BergerDefence Research and Development CanadaVerified email at drdc-rddc.gc.ca
Abdellah Chehri, PhD, IEEE Senior M...Professor, Royal Military College of Canada/ University of OttawaVerified email at rmc.ca
Eduardo AlonsoProfessor of Artificial Intelligence; City, University of LondonVerified email at city.ac.uk
Mohammed Hamada GasmallahQueen's UniversityVerified email at queensu.ca
Gwanggil JeonIncheon National UniversityVerified email at inu.ac.kr
Hussein T. MouftahProfessor of Electrical Engineering and Computer ScienceVerified email at site.uottawa.ca
Donghao QiaoQueen's UniversityVerified email at queensu.ca

Francois Rivest

Professor, Mathematics and Computer Science, Royal Military College of Canada

Verified email at rmc.ca - Homepage

Artificial intelligence Machine learning Reinforcement Learning Dopamine Interval Timing


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Knowledge-based cascade-correlation: Using knowledge to speed learning TR Shultz, F Rivest Connection Science 13 (1), 43-72, 2001	117	2001
Timescale invariance in the pacemaker-accumulator family of timing models P Simen, F Rivest, EA Ludvig, F Balci, P Killeen Timing & Time Perception 1 (2), 159-188, 2013	108*	2013
Application of knowledge-based cascade-correlation to vowel recognition F Rivest, TR Shultz Proceedings of the 2002 International Joint Conference on Neural Networks …, 2002	51	2002
Combining TD-learning with cascade-correlation networks F Rivest, D Precup Proceedings of the twentieth International Conference on Machine Learning 20 …, 2003	49	2003
An adaptive drift-diffusion model of interval timing dynamics A Luzardo, EA Ludvig, F Rivest Behavioural processes 95, 90-99, 2013	45	2013
Adaptive Drift-Diffusion Process to Learn Time Intervals F Rivest, Y Bengio Arxiv preprint arXiv:1103.2382, 2011	33	2011
Spiking neurons, dopamine, and plasticity: timing is everything, but concentration also matters JP Thivierge, F Rivest, O Monchi Synapse 61 (6), 375-390, 2007	33	2007
Brain inspired reinforcement learning F Rivest, Y Bengio, J Kalaska Advances in neural information processing systems 17, 1129-1136, 2005	33	2005
Alternative time representation in dopamine models F Rivest, JF Kalaska, Y Bengio Journal of computational neuroscience 28 (1), 107-130, 2010	28	2010
A new timing error cost function for binary time series prediction F Rivest, R Kohar IEEE transactions on neural networks and learning systems 31 (1), 174-185, 2019	24	2019
Deep reinforcement learning for multi-satellite collection scheduling JT Lam, F Rivest, J Berger Theory and Practice of Natural Computing: 8th International Conference, TPNC …, 2019	23	2019
Could knowledge-based neural learning be useful in developmental robotics? The case of KBCC TR Shultz, F Rivest, L Egri, JP Thivierge, F Dandurand International Journal of Humanoid Robotics 4 (02), 245-279, 2007	23	2007
A dual-phase technique for pruning constructive networks JP Thivierge, F Rivest, TR Shultz Proceedings of the International Joint Conference on Neural Networks, 2003 …, 2003	23	2003
Using Knowledge to Speed Learning: A Comparison of Knowledge-based Cascade-correlation and Multi-task Learning. TR Shultz, F Rivest Proceeding of the Seventeenth International Conference on Machine Learning …, 2000	23*	2000
Knowledge-based cascade corellation T Schultz, F Rivest Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural …, 2000	21	2000
A drift–diffusion model of interval timing in the peak procedure A Luzardo, F Rivest, E Alonso, EA Ludvig Journal of Mathematical Psychology 77, 111-123, 2017	20	2017
Conditioning and time representation in long short-term memory networks F Rivest, JF Kalaska, Y Bengio Biological cybernetics 108 (1), 23-48, 2014	19	2014
Potential Impacts of Smart Homes on Human Behavior: A Reinforcement Learning Approach S Suman, A Etemad, F Rivest IEEE Transactions on Artificial Intelligence, 2021	15	2021
Complex problem solving with reinforcement learning F Dandurand, TR Shultz, F Rivest Development and Learning, 2007. ICDL 2007. IEEE 6th International Conference …, 2007	12	2007
Knowledge-based Learning with KBCC TR Shultz, F Rivest, L Egri, JP Thivierge Proceedings of the Fifth International Conference on Development and …, 2006	10	2006

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