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ORCIDGuillaume Lajoie
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2020 – today
- 2022
[j10]Matthew Farrell
, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mach. Intell. 4(6): 564-573 (2022)- [j9]Maximilian Puelma Touzel, Paul Cisek, Guillaume Lajoie:
Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost. PLoS Comput. Biol. 18(5) (2022) - [c14]Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP 2022: 5647-5651 - [c13]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. ICLR 2022 - [c12]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. ICLR 2022 - [c11]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. ICML 2022: 17669-17690 - [c10]Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA 2022: 171-184 - [c9]Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy:
Learning Shared Neural Manifolds from Multi-Subject FMRI Data. MLSP 2022: 1-6 - [i25]Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy:
Learning shared neural manifolds from multi-subject FMRI data. CoRR abs/2201.00622 (2022) - [i24]Léo Gagnon, Guillaume Lajoie:
Clarifying MCMC-based training of modern EBMs : Contrastive Divergence versus Maximum Likelihood. CoRR abs/2202.12176 (2022) - [i23]Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon:
Continuous-Time Meta-Learning with Forward Mode Differentiation. CoRR abs/2203.01443 (2022) - [i22]Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie:
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR abs/2206.00823 (2022) - [i21]Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie:
Is a Modular Architecture Enough? CoRR abs/2206.02713 (2022) - [i20]Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie:
On Neural Architecture Inductive Biases for Relational Tasks. CoRR abs/2206.05056 (2022) - [i19]Thomas George, Guillaume Lajoie, Aristide Baratin:
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. CoRR abs/2209.09658 (2022) - [i18]Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou:
From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR abs/2210.13774 (2022) - [i17]MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky:
Reliability of CKA as a Similarity Measure in Deep Learning. CoRR abs/2210.16156 (2022) - [i16]Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake A. Richards:
Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. CoRR abs/2211.16607 (2022) - 2021
- [j8]Laura E. Suárez, Blake A. Richards, Guillaume Lajoie, Bratislav Misic:
Learning function from structure in neuromorphic networks. Nat. Mach. Intell. 3(9): 771-786 (2021) - [j7]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, Irina Rish:
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33(8): 2087-2127 (2021) - [c8]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization via Neural Feature Alignment. AISTATS 2021: 2269-2277 - [c7]Olivier Tessier-Larivière, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie, Blake A. Richards:
PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks. NER 2021: 778-782 - [c6]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c5]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS 2021: 1256-1272 - [i15]Christian David Marton, Guillaume Lajoie, Kanaka Rajan:
Efficient and robust multi-task learning in the brain with modular task primitives. CoRR abs/2105.14108 (2021) - [i14]Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal:
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR abs/2107.00848 (2021) - [i13]Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy:
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR abs/2107.12334 (2021) - [i12]Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie:
Compositional Attention: Disentangling Search and Retrieval. CoRR abs/2110.09419 (2021) - [i11]Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie:
Multi-scale Feature Learning Dynamics: Insights for Double Descent. CoRR abs/2112.03215 (2021) - 2020
- [c4]Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie:
Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. Canadian Conference on AI 2020: 276-282 - [c3]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML 2020: 6972-6986 - [c2]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS 2020 - [i10]Stefan Horoi, Guillaume Lajoie, Guy Wolf:
Internal representation dynamics and geometry in recurrent neural networks. CoRR abs/2001.03255 (2020) - [i9]Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie:
Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR abs/2006.09471 (2020) - [i8]Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf, Guillaume Lajoie:
Advantages of biologically-inspired adaptive neural activation in RNNs during learning. CoRR abs/2006.12253 (2020) - [i7]Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie:
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. CoRR abs/2006.14123 (2020) - [i6]Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio:
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR abs/2006.16981 (2020) - [i5]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization in Deep Learning: A View from Function Space. CoRR abs/2008.00938 (2020) - [i4]Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas:
LEAD: Least-Action Dynamics for Min-Max Optimization. CoRR abs/2010.13846 (2020) - [i3]Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie:
Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR abs/2011.09468 (2020)
2010 – 2019
- 2019
- [c1]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS 2019: 13591-13601 - [i2]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR abs/1905.12080 (2019) - [i1]Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown:
Dimensionality compression and expansion in Deep Neural Networks. CoRR abs/1906.00443 (2019) - 2017
- [j6]Guillaume Lajoie, Nedialko I. Krouchev, John F. Kalaska, Adrienne L. Fairhall, Eberhard E. Fetz:
Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface. PLoS Comput. Biol. 13(2) (2017) - 2016
- [j5]Philippe Vincent-Lamarre, Guillaume Lajoie, Jean-Philippe Thivierge:
Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks. J. Comput. Neurosci. 41(3): 305-322 (2016) - [j4]Guillaume Lajoie, Lai-Sang Young:
Dynamic Signal Tracking in a Simple V1 Spiking Model. Neural Comput. 28(9): 1985-2010 (2016) - [j3]Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown:
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. PLoS Comput. Biol. 12(12) (2016) - 2014
- [j2]Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown:
Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. 8: 123 (2014) - 2011
- [j1]Guillaume Lajoie, Eric Shea-Brown:
Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps. SIAM J. Appl. Dyn. Syst. 10(4): 1232-1271 (2011)
Coauthor Index
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last updated on 2022-12-03 23:01 CET by the dblp team
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