François Laviolette
François Laviolette
Université Laval, Associate member at MILA, AI CIFAR Chair
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Cited by
Cited by
Domain-adversarial training of neural networks
Y Ganin, E Ustinova, H Ajakan, P Germain, H Larochelle, F Laviolette, ...
The journal of machine learning research 17 (1), 2096-2030, 2016
Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species
KR Bradnam, JN Fass, A Alexandrov, P Baranay, M Bechner, I Birol, ...
GigaScience 2 (1), 2047-217X-2-10, 2013
Ray Meta: scalable de novo metagenome assembly and profiling
S Boisvert, F Raymond, É Godzaridis, F Laviolette, J Corbeil
Genome biology 13 (12), 1-13, 2012
Ray: simultaneous assembly of reads from a mix of high-throughput sequencing technologies
S Boisvert, F Laviolette, J Corbeil
Journal of computational biology 17 (11), 1519-1533, 2010
Deep learning for electromyographic hand gesture signal classification using transfer learning
U Côté-Allard, CL Fall, A Drouin, A Campeau-Lecours, C Gosselin, ...
IEEE transactions on neural systems and rehabilitation engineering 27 (4 …, 2019
Domain-adversarial neural networks
H Ajakan, P Germain, H Larochelle, F Laviolette, M Marchand
arXiv preprint arXiv:1412.4446, 2014
PAC-Bayesian learning of linear classifiers
P Germain, A Lacasse, F Laviolette, M Marchand
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
Transfer learning for sEMG hand gestures recognition using convolutional neural networks
U Côté-Allard, CL Fall, A Campeau-Lecours, C Gosselin, F Laviolette, ...
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2017
Risk bounds for the majority vote: From a PAC-Bayesian analysis to a learning algorithm
P Germain, A Lacasse, F Laviolette, M Marchand, JF Roy
arXiv preprint arXiv:1503.08329, 2015
A PAC-Bayesian approach for domain adaptation with specialization to linear classifiers
P Germain, A Habrard, F Laviolette, E Morvant
International conference on machine learning, 738-746, 2013
A convolutional neural network for robotic arm guidance using sEMG based frequency-features
UC Allard, F Nougarou, CL Fall, P Giguère, C Gosselin, F Laviolette, ...
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
Bisimulation and cocongruence for probabilistic systems
V Danos, J Desharnais, F Laviolette, P Panangaden
Information and Computation 204 (4), 503-523, 2006
Approximate analysis of probabilistic processes: Logic, simulation and games
J Desharnais, F Laviolette, M Tracol
2008 Fifth International Conference on Quantitative Evaluation of Systems …, 2008
PAC-Bayes bounds for the risk of the majority vote and the variance of the Gibbs classifier
A Lacasse, F Laviolette, M Marchand, P Germain, N Usunier
Advances in Neural information processing systems 19, 2006
PAC-Bayesian inequalities for martingales
Y Seldin, F Laviolette, N Cesa-Bianchi, J Shawe-Taylor, P Auer
IEEE Transactions on Information Theory 58 (12), 7086-7093, 2012
Tighter PAC-Bayes bounds through distribution-dependent priors
G Lever, F Laviolette, J Shawe-Taylor
Theoretical Computer Science 473, 4-28, 2013
Predictive computational phenotyping and biomarker discovery using reference-free genome comparisons
A Drouin, S Giguère, M Déraspe, M Marchand, M Tyers, VG Loo, ...
BMC genomics 17 (1), 1-15, 2016
Predicting ion mobility collision cross-sections using a deep neural network: DeepCCS
PL Plante, É Francovic-Fontaine, JC May, JA McLean, ES Baker, ...
Analytical chemistry 91 (8), 5191-5199, 2019
Interpretable genotype-to-phenotype classifiers with performance guarantees
A Drouin, G Letarte, F Raymond, M Marchand, J Corbeil, F Laviolette
Scientific reports 9 (1), 1-13, 2019
Canadian Association of Radiologists white paper on ethical and legal issues related to artificial intelligence in radiology
Canadian Association of Radiologists (CAR) Artificial Intelligence Working Group
Canadian Association of Radiologists' Journal 70 (2), 107-118, 2019
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