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Selected Preprints
Selected Preprints
Discrete, compositional, and symbolic representations through attractor dynamics, Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie [preprint: https://arxiv.org/abs/2310.01807].
Amortizing intractable inference in large language models, Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin [preprint: https://arxiv.org/abs/2310.04363].
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency, Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan [preprint: https://arxiv.org/abs/2310.03734].
Delta-AI: Local objectives for amortized inference in sparse graphical models, Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio [preprint: https://arxiv.org/abs/2310.02423].
Online Bayesian Optimization of Nerve Stimulation, Lorenz Wernisch, Tristan Edwards, Antonin Berthon, Olivier Tessier-Lariviere, Elvijs Sarkans, Myrta Stoukidi, Pascal Fortier-Poisson, Max Pinkney, Michael Thornton, Hanley Catherine, Susannah Lee, Joel Jennings, Ben Appleton, Phillip Garsed, Bret Patterson, Buttinger Will, Samuel Gonshaw, Matjaž Jakopec, Sudhakaran Shunmugam, Jorin Mamen, Aleksi Tukiainen, Guillaume Lajoie, Oliver Armitage, Emil Hewage [preprint: https://www.biorxiv.org/content/10.1101/2023.08.30.555315v1].
Using neural biomarkers to personalize dosing of vagus nerve stimulation, Antoninn Berthon, Lorenz Wernisch, Myrta Stoukidi, Michael Thornton, Olivier Tessier-Lariviere, Pascal Fortier-Poisson, Jorin Mamen, Max Pinkney, Susannah Lee, Elvijs Sarkans, Luca Annecchino, Ben Appleton, Philip Garsed, Bret Patterson, Samuel Gonshaw, Matjaz Jakopec, Sudhakaran Shunmugam, Tristan Edwards, Aleksi Tukiainen, Joel Jennings, Guillaume Lajoie, Emil Hewage, Oliver Armitage [preprint: https://www.biorxiv.org/content/10.1101/2023.08.30.555487v1].
Synaptic Weight Distributions Depend on the Geometry of Plasticity, Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Richards [preprint: https://arxiv.org/abs/2305.19394].
Neural manifolds and gradient-based adaptation in neural-interface tasks, Alexandre Payeur, Amy L. Orsborn, Guillaume Lajoie [preprint: https://www.biorxiv.org/content/10.1101/2023.03.11.532146v1].
Sources of Richness and Ineffability for Phenomenally Conscious States, Xu Ji, Eric Elmoznino, George Deane, Axel Constant, Guillaume Dumas, Guillaume Lajoie, Jonathan Simon, Yoshua Bengio [preprint: https://arxiv.org/abs/2302.06403].
From points to functions: infinite-dimensional representations in diffusion models, Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou, [preprint: https://arxiv.org/abs/2210.13774]
Rapidly Inferring Personalized Neurostimulation Parameters with Meta-Learning: A Case Study of Individualized Fiber Recruitment in Vagus Nerve Stimulation, Ximeng Mao, Yao-Chuan Chang, Stavros Zanos, Guillaume Lajoie, [preprint: https://www.biorxiv.org/content/10.1101/2022.09.06.506839v1]
On Neural Architecture Inductive Biases for Relational Tasks, Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake Richards, Guillaume Lajoie, [preprint: https://arxiv.org/abs/2206.05056]
Goal-driven optimization of single-neuron properties in artificial networks reveals regularization role of neural diversity and adaptation, Victor Geadah, Stefan Horoi, Giancarlo Kerg, Guy Wolf, Guillaume Lajoie, [preprint: https://www.biorxiv.org/content/10.1101/2022.04.29.489963v1]
Efficient and robust multi-task learning in the brain with modular task primitives, C. D. Marton, G. Lajoie, K. Rajan [preprint: https://arxiv.org/abs/2105.14108].
Lagrangian-based Dynamics for Game Optimization, R. Askari, A. Mitra, G. Lajoie, I. Mitliagkas, [preprint: https://arxiv.org].
Transcranial DC stimulation affects population dynamics and single cell firing rate but not tuning in macaque sensorimotor cortex, Andrew R. Bogaard, Guillaume Lajoie, Hayley Boyd, Andrew Morse, Stavros Zanos, Eberhard E. Fetz, [preprint: https://www.biorxiv.org/content/10.1101/516260v2].
Selected Published Articles
Selected Published Articles
Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie
ICML 2023
Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie*, Blake Richards*
TMLR 2023
Marco Bonizzato, Sandrine L. Cote, Elena Massai, Rose Guay-Hottin, Samuel Laferriere, Stephan Quessy, Guillaume Lajoie*, Marina Martinez*, Numa Dancause
Cell Reports Medecine 2023
Thomas George, Guillaume Lajoie, Aristide Baratin
TMRL 2023
Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
NeurIPS 2022
Laura E. Suarez, Yossi Yovel, Martijn P. van den Heuvel, Olaf Sporns, Yaniv Assaf, Guillaume Lajoie, Bratislav Misic
eLife (2022)
Maximilian Puelma Touzel, Paul Cisek, Guillaume Lajoie
PLoS Computationa Biology (2022)
Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, and Eric Shea-Brown
Nature Machine Intelligence (2022)
Jessie Huang, Erica Busch, Michal Gerasimiuk, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Nick Turk-Browne, and Smita Krishnaswamy
IEEE MLSP 2022
Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, and Guillaume Lajoie
ICML 2022
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie,
(spotlight presentation) ICLR 2022
Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon,
(spotlight presentation), ICLR 2022
Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman and Guillaume Lajoie,
Frontiers in Applied Mathematics and Statistics, 2022
M. Pezeshki, S.O. Kaba, Y. Bengio, A. Courville, D. Precup, G. Lajoie, NeurIPS 2021
A. Baratin, T. George, C. Laurent, V. Thomas, D. Hjelm, G. Lajoie, P. Vincent, S. Lacoste-Julien, (AISTAT) 2021
Olivier Tessier-Lariviere, Luke Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Emil Hewage, Oli Armitage, Guillaume Lajoie*, Blake Richards*, 10th International IEEE EMBS Conference On Neural Engineering (NER21) 2021
*co-senior authors
E. Suarez, B.A. Richards, G. Lajoie, B. Misic, Nature Machine Intelligence 3, 771–786 (2021).
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti, Eric Shea-Brown, Nat Commun 12, 1417 (2021).
German Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James Kozloski, Pablo Polosecki, Guillaume Lajoie, David Cox, Silvina Ponce Dawson, Guillermo Cecchi, Irina Rish, Neural Computations, (2021)
Samuel Laferrière, Marco Bonizzato, Numa Dancause, and Guillaume Lajoie, IEEE Brain BrainInsight, Issue 2, (2020).
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie, Accepted at Neural Information Processing Systems (NeurIPS), (2020).
Learning complex motor control with neurostimulation: a hierarchical and adaptive algorithm to optimally explore neural maps
Learning complex motor control with neurostimulation: a hierarchical and adaptive algorithm to optimally explore neural maps
Samuel Laferrière, Marco Bonizzato, Sandrine Côté, Numa Dan- cause, and Guillaume Lajoie, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 6, pp. 1452-1460, June 2020
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Net- works with Attention over Modules
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Net- works with Attention over Modules
S. Mittal, A. Lamb, A. Goyal, V. Voleti, M. Shanahan, G. Lajoie, M. Mozer, Y. Bengio, International Conference of Machine Learning (ICML), (2020).
Low-dimensional dynamics of encoding and learning in recurrent neural networks
Low-dimensional dynamics of encoding and learning in recurrent neural networks
Stefan Horoi, Victor Geadah, Guy Wolf, and Guillaume Lajoie, Advances in Artificial Intelligence (proceedings of CanadianAI 2020), Chapter No: 27, DOI:10.1007/978-3-030-47358-7_27
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Giancarlo Kerg, Kyle Goyette, Max- imilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, and Guillaume Lajoie, 33rd Conference on Neural Information Processing Systems (NeurIPS), (2019), arxiv.org/abs/ 1905.12080.
Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional Brain-Machine Interface
Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional Brain-Machine Interface
Guillaume Lajoie, Nedialko Krouchev, John F. Kalaska, Adrienne Fairhall, Eberhard E. Fetz, PLoS Comput. Biol., (2017), Vol. 13, No. 2, Pages e1005343- 34, DOI:10.1371/journal.pcbi.1005343
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus- Driven Systems
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus- Driven Systems
Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown, PLoS Comput. Biol., (2016), Vol. 12, No. 12, Pages e1005258-30, DOI: 10.1371/journal.pcbi. 1005258
Dynamic signal tracking in a simple V1 spiking model
Dynamic signal tracking in a simple V1 spiking model
Guillaume Lajoie, Lai-Sang Young, Neural Computation, (2016), Vol. 28, No. 9, Pages 1985-2010, DOI: 10.1162/NECO_a_00868
Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks
Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks
Philippe Vincent-Lamarre, Guillaume Lajoie, Jean-Philippe Thivierge, J Comput Neurosci, (2016), DOI: 10.1007/s10827-016-0619-3
Structured chaos shapes spike-response noise entropy in balanced neural networks
Structured chaos shapes spike-response noise entropy in balanced neural networks
Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown, Frontiers in Computational Neuro- science, (2014), vol. 8, pp 1-10, DOI: 10.3389/fncom.2014.00123
Chaos and reliability in balanced spiking networks with temporal drive
Chaos and reliability in balanced spiking networks with temporal drive
Guillaume Lajoie, Kevin K. Lin, Eric Shea-Brown, Phys. Rev. E, (2013), vol. 87 (5), p. 052901, DOI: 10.1103/ PhysRevE.87.052901
Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Pas- sage to Discontinuous Circle Maps
Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Pas- sage to Discontinuous Circle Maps
Guillaume Lajoie, Eric Shea-Brown, SIAM Journal of Applied Dynamical Systems, (2011), vol. 10, p. 1232, DOI: 10.1137/100811726
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