Publications

see CV or Google Scholar for complete and up-to-date list

Preprints

  • 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]

  • Multi-scale Feature Learning Dynamics: Insights for Double Descent, Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie, [preprint: https://arxiv.org/abs/ 2112.03215]

  • Compositional Attention: Disentangling Search and Retrieval, Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie, [preprint: https://arxiv.org/ abs/2110.09419]

  • Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover’s Distance, Alexander Tong, Guillaume Huguet, Dennis Shung, Amine Natik, Manik Kuchroo, Guil- laume Lajoie, Guy Wolf, Smita Krishnaswamy, [preprint: https://arxiv.org/abs/2107.12334]

  • 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].

  • Advantages of biologically-inspired adaptive neural activation in RNNs during learning, V. Geadah, G. Kerg, S. Horoi, G. Wolf, G. Lajoie, [preprint: arxiv.org/abs/2006.12253].

  • On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools, R. Vogt, M. Puelma Touzel, E. Shlizerman, G. Lajoie, [preprint: https://arxiv.org/abs/2006.14123].

  • Lagrangian-based Dynamics for Game Optimization, R. Askari, A. Mitra, G. Lajoie, I. Mitliagkas, [preprint: https://arxiv.org].

  • Dynamic compression and expansion in a classifying recurrent network, Matthew Farrell, Stefano Recanatesi, Guillaume Lajoie and Eric Shea-Brown, . [preprint: https://www.biorxiv.org/content/10.1101/564476v1].

  • 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

Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, and Eric Shea-Brown

Nature Machine Intelligence (2022)

Maximilian Puelma Touzel, Paul Cisek, Guillaume Lajoie

PLoS Computationa Biology (2022)

Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie, (spotlight presentation), ICML 2022

Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon, (spotlight presentation), ICML 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

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

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

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

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

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

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

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

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

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

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

Guillaume Lajoie, Eric Shea-Brown, SIAM Journal of Applied Dynamical Systems, (2011), vol. 10, p. 1232, DOI: 10.1137/100811726