Francois Rivest
Francois Rivest
Professor, Mathematics and Computer Science, Royal Military College of Canada
Verified email at - Homepage
Cited by
Cited by
Knowledge-based cascade-correlation: Using knowledge to speed learning
TR Shultz, F Rivest
Connection Science 13 (1), 43-72, 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
Application of knowledge-based cascade-correlation to vowel recognition
F Rivest, TR Shultz
Proceedings of the 2002 International Joint Conference on Neural Networks …, 2002
Combining TD-learning with cascade-correlation networks
F Rivest, D Precup
Proceedings of the twentieth International Conference on Machine Learning 20 …, 2003
An adaptive drift-diffusion model of interval timing dynamics
A Luzardo, EA Ludvig, F Rivest
Behavioural processes 95, 90-99, 2013
Adaptive Drift-Diffusion Process to Learn Time Intervals
F Rivest, Y Bengio
Arxiv preprint arXiv:1103.2382, 2011
Brain inspired reinforcement learning
F Rivest, Y Bengio, J Kalaska
Advances in neural information processing systems 17, 1129-1136, 2005
Spiking neurons, dopamine, and plasticity: timing is everything, but concentration also matters
JP Thivierge, F Rivest, O Monchi
Synapse 61 (6), 375-390, 2007
Alternative time representation in dopamine models
F Rivest, JF Kalaska, Y Bengio
Journal of computational neuroscience 28 (1), 107-130, 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
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
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
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
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
Knowledge-based cascade corellation
T Schultz, F Rivest
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural …, 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
Conditioning and time representation in long short-term memory networks
F Rivest, JF Kalaska, Y Bengio
Biological cybernetics 108 (1), 23-48, 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
Complex problem solving with reinforcement learning
F Dandurand, TR Shultz, F Rivest
Development and Learning, 2007. ICDL 2007. IEEE 6th International Conference …, 2007
Knowledge-based Learning with KBCC
TR Shultz, F Rivest, L Egri, JP Thivierge
Proceedings of the Fifth International Conference on Development and …, 2006
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