Guillaume Lajoie

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Membre Académique Principal
Guillaume Lajoie
Professeur adjoint, Université de Montréal
Guillaume Lajoie

Guillaume Lajoie est professeur adjoint au Département de mathématiques et de statistique (DMS) de l’Université de Montréal et membre académique principal de Mila.  Il est également titulaire d’une position de chercheur boursier du FRQS. Il était auparavant boursier postdoctoral au Max Planck Institute for Dynamics and Self-Organization et à l’Université de Washington Institute for Neuroengineering et il a obtenu son doctorat au Département de mathématiques appliquées de l’Université de Washington, à Seattle.

Sa recherche est centrée à l’intersection de l’IA et des neurosciences où il s’intéresse à des questions reliées à la dynamiques et aux computations de réseaux neuronaux, avec certaines applications à la neuroingénérie. Ses travaux récents comprennent le développement de biais inductifs pour un meilleure propagation d’information dans les réseaux récurrents, ainsi que le développement d’algorithmes pour optimiser les interfaces cerveau-machine bidirectionnelles.

Publications

2021-09

Learning function from structure in neuromorphic networks
Laura E. Suárez, Blake A. Richards, Guillaume Lajoie and Bratislav Misic
Nature Machine Intelligence
(2021-09-01)
europepmc.org[Also on bioRxiv (2020-11-11)]

2021-07

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.
Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf and Smita Krishnaswamy
arXiv preprint arXiv:2107.12334
(2021-07-26)
ui.adsabs.harvard.eduPDF
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.
German Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi and Irina Rish
Neural Computation
(2021-07-26)
direct.mit.edu

2021-05

Efficient and robust multi-task learning in the brain with modular task primitives.
Christian David Marton, Guillaume Lajoie and Kanaka Rajan
arXiv preprint arXiv:2105.14108
(2021-05-28)
ui.adsabs.harvard.eduPDF
PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks
Olivier Tessier-Lariviere, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie and Blake A. Richards
NER 2021
(2021-05-04)
ieeexplore.ieee.org
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
Nan Rosemary Ke, Aniket Rajiv Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Curtis Mozer, Yoshua Bengio and Christopher Pal
arxiv:stat.ML
(2021-05-04)
dblp.uni-trier.dePDF

2021-03

Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent and Simon Lacoste-Julien
Predictive learning as a network mechanism for extracting low-dimensional latent space representations.
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti and Eric Shea-Brown
Nature Communications
(2021-03-03)
europepmc.org[Also on bioRxiv (2020-09-17)]

2020-11

Gradient Starvation: A Learning Proclivity in Neural Networks.
Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup and Guillaume Lajoie
arXiv preprint arXiv:2011.09468
(2020-11-18)
ui.adsabs.harvard.eduPDF

2020-10

LEAD: Least-Action Dynamics for Min-Max Optimization
Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie and Ioannis Mitliagkas
arXiv preprint arXiv:2010.13846
(2020-10-26)
onikle.comPDF

2020-08

Implicit Regularization in Deep Learning: A View from Function Space.
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent and Simon Lacoste-Julien
(venue unknown)
(2020-08-03)
www.microsoft.com

2020-07

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer and Yoshua Bengio

2020-06

On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman and Guillaume Lajoie
arXiv preprint arXiv:2006.14123
(2020-06-25)
ui.adsabs.harvard.eduPDF
Advantages of biologically-inspired adaptive neural activation in RNNs during learning.
Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf and Guillaume Lajoie
arXiv preprint arXiv:2006.12253
(2020-06-22)
dblp.uni-trier.dePDF
Untangling tradeoffs between recurrence and self-attention in neural networks
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio and Guillaume Lajoie
arXiv preprint arXiv:2006.09471
(2020-06-16)
ui.adsabs.harvard.eduPDF

2020-05

Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks
Stefan Horoi, Victor Geadah, Guy Wolf and Guillaume Lajoie
AI 2020
(2020-05-13)
doi.org

2020-04

Hierarchical Bayesian Optimization of Spatiotemporal Neurostimulations for Targeted Motor Outputs
Samuel Laferriere, Marco Bonizzato, Sandrine L. Cote, Numa Dancause and Guillaume Lajoie
EMBC 2020
(2020-04-13)
ieeexplore.ieee.org

2020-01

Internal representation dynamics and geometry in recurrent neural networks.
Stefan Horoi, Guillaume Lajoie and Guy Wolf
arXiv preprint arXiv:2001.03255
(2020-01-09)
ui.adsabs.harvard.eduPDF
Untangling tradeoffs between recurrence and self-attention in artificial neural networks
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal Alias Parth Goyal, Kyle Goyette, Yoshua Bengio and Guillaume Lajoie
NEURIPS 2020
(2020-01-01)
papers.nips.ccPDF

2019-09

Recurrent neural networks learn robust representations by dynamically balancing compression and expansion
Matthew Farrell, Stefano Recanatesi, Guillaume Lajoie and Eric Shea-Brown
bioRxiv
(2019-09-11)
openreview.netPDF
Modelling Working Memory using Deep Recurrent Reinforcement Learning
Pravish Sainath, Pierre Bellec and Guillaume Lajoie
(venue unknown)
(2019-09-11)
openreview.netPDF

2019-07

Predictive learning extracts latent space representations from sensory observations
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti and Eric Shea-Brown
bioRxiv
(2019-07-13)
www.biorxiv.orgPDF

2019-06

Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm
Samuel Laferriere, Marco Bonizzato, Numa Dancause and Guillaume Lajoie
bioRxiv
(2019-06-11)
www.biorxiv.orgPDF
Dimensionality compression and expansion in Deep Neural Networks.
Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie and Eric Shea-Brown
arXiv preprint arXiv:1906.00443
(2019-06-02)
ui.adsabs.harvard.eduPDF

2019-03

Dynamic compression and expansion in a classifying recurrent network
Matthew Farrell, Stefano Recanatesi, Guillaume Lajoie and Eric Shea-Brown
bioRxiv
(2019-03-01)
www.biorxiv.orgPDF

2019-01

Cortical network mechanisms of anodal and cathodal transcranial direct current stimulation in awake primates
Andrew R. Bogaard, Guillaume Lajoie, Hayley Boyd, Andrew Morse, Stavros Zanos and Eberhard E. Fetz
bioRxiv
(2019-01-09)
www.biorxiv.orgPDF
Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm.
Samuel Laferriere, Guillaume Lajoie, Numa Dancause and Marco Bonizzato
2019 Conference on Cognitive Computational Neuroscience
(2019-01-01)
dx.doi.org
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio and Guillaume Lajoie

2018-11

Signatures and mechanisms of low-dimensional neural predictive manifolds
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti and Eric Shea-Brown
bioRxiv
(2018-11-17)
www.biorxiv.orgPDF

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