Guillaume Lajoie

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Eric Shea-BrownApplied Mathematics, University of WashingtonAdresse e-mail validée de uw.edu
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARAdresse e-mail validée de umontreal.ca
Stefano RecanatesiUniversity of WashingtonAdresse e-mail validée de uw.edu
Giancarlo KergPhD Student, MILA, Université de MontréalAdresse e-mail validée de umontreal.ca
JP ThiviergeAssociate professor of Psychology, University of OttawaAdresse e-mail validée de uottawa.ca
Kevin K. LinAssociate Professor of Mathematics, University of ArizonaAdresse e-mail validée de math.arizona.edu
Maximilian Puelma TouzelMila, Universite de MontrealAdresse e-mail validée de mila.quebec
Mattia RigottiResearcher at IBM Research AIAdresse e-mail validée de columbia.edu
Philippe Vincent-LamarreUniversité de MontréalAdresse e-mail validée de umontreal.ca
Eberhard E FetzProfessor of Physiology & Biophysics and DXARTS, University of WashingtonAdresse e-mail validée de uw.edu
Gauthier GidelAssistant professor at Mila, University of Montréal (DIRO)Adresse e-mail validée de umontreal.ca
Eugene VorontsovEcole Polytechnique de MontrealAdresse e-mail validée de polymtl.ca
Adrienne FairhallProfessor of Physiology and Biophysics, University of WashingtonAdresse e-mail validée de uw.edu
John F. KalaskaUniversité de MontréalAdresse e-mail validée de umontreal.ca
Nedialko KrouchevMontreal Neurological Institute and HospitalAdresse e-mail validée de mcgill.ca
Andrew BogaardMedical Scientist Training Program, University of WashingtonAdresse e-mail validée de uw.edu
Stavros ZanosAssociate Professor, Feinstein Institute for Medical ResearchAdresse e-mail validée de northwell.edu

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Guillaume Lajoie

Assistant Professor, Applied Mathematics, Université de Montréal

Adresse e-mail validée de umontreal.ca - Page d'accueil

dynamical systems computation neuroscience network dynamics AI


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Chaos and reliability in balanced spiking networks with temporal drive G Lajoie, KK Lin, E Shea-Brown Physical Review E 87 (5), 052901, 2013	47	2013
Gradient starvation: A learning proclivity in neural networks M Pezeshki, O Kaba, Y Bengio, AC Courville, D Precup, G Lajoie Advances in Neural Information Processing Systems 34, 2021	42	2021
Non-normal recurrent neural network (nnrnn): learning long time dependencies while improving expressivity with transient dynamics G Kerg, K Goyette, M Puelma Touzel, G Gidel, E Vorontsov, Y Bengio, ... Advances in neural information processing systems 32, 2019	41	2019
Dimensionality compression and expansion in deep neural networks S Recanatesi, M Farrell, M Advani, T Moore, G Lajoie, E Shea-Brown arXiv preprint arXiv:1906.00443, 2019	31	2019
Learning to combine top-down and bottom-up signals in recurrent neural networks with attention over modules S Mittal, A Lamb, A Goyal, V Voleti, M Shanahan, G Lajoie, M Mozer, ... International Conference on Machine Learning, 6972-6986, 2020	30	2020
Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks P Vincent-Lamarre, G Lajoie, JP Thivierge Journal of computational neuroscience 41 (3), 305-322, 2016	20	2016
Structured chaos shapes spike-response noise entropy in balanced neural networks G Lajoie, JP Thivierge, E Shea-Brown Frontiers in computational neuroscience 8, 123, 2014	20	2014
Encoding in balanced networks: Revisiting spike patterns and chaos in stimulus-driven systems G Lajoie, KK Lin, JP Thivierge, E Shea-Brown PLoS computational biology 12 (12), e1005258, 2016	16	2016
Learning function from structure in neuromorphic networks LE Suárez, BA Richards, G Lajoie, B Misic Nature Machine Intelligence 3 (9), 771-786, 2021	15	2021
Shared inputs, entrainment, and desynchrony in elliptic bursters: From slow passage to discontinuous circle maps G Lajoie, E Shea-Brown SIAM Journal on Applied Dynamical Systems 10 (4), 1232-1271, 2011	14	2011
On lyapunov exponents for rnns: Understanding information propagation using dynamical systems tools R Vogt, MP Touzel, E Shlizerman, G Lajoie arXiv preprint arXiv:2006.14123, 2020	13	2020
Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface G Lajoie, NI Krouchev, JF Kalaska, AL Fairhall, EE Fetz PLoS computational biology 13 (2), e1005343, 2017	13	2017
Dynamic compression and expansion in a classifying recurrent network MS Farrell, S Recanatesi, G Lajoie, E Shea-Brown bioRxiv, 564476, 2019	11	2019
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion M Farrell, S Recanatesi, T Moore, G Lajoie, E Shea-Brown bioRxiv, 564476, 2019	11	2019
Predictive learning as a network mechanism for extracting low-dimensional latent space representations S Recanatesi, M Farrell, G Lajoie, S Deneve, M Rigotti, E Shea-Brown Nature communications 12 (1), 1-13, 2021	10	2021
Implicit regularization via neural feature alignment A Baratin, T George, C Laurent, RD Hjelm, G Lajoie, P Vincent, ... International Conference on Artificial Intelligence and Statistics, 2269-2277, 2021	8	2021
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion. bioRxiv M Farrell, S Recanatesi, T Moore, G Lajoie, E Shea-Brown December 3, 564476, 2019	8	2019
Lead: Least-action dynamics for min-max optimization RA Hemmat, A Mitra, G Lajoie, I Mitliagkas arXiv preprint arXiv:2010.13846, 2020	6	2020
Cortical network mechanisms of anodal and cathodal transcranial direct current stimulation in awake primates AR Bogaard, G Lajoie, H Boyd, A Morse, S Zanos, EE Fetz bioRxiv, 516260, 2019	6	2019
Predictive learning extracts latent space representations from sensory observations S Recanatesi, M Farrell, G Lajoie, S Deneve, M Rigotti, E Shea-Brown bioRxiv, 2019	5	2019

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