Guillaume Lajoie

Orcid: 0000-0003-2730-7291

According to our database¹, Guillaume Lajoie authored at least 55 papers between 2011 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2023

Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer.

[BibT_eX]

[DOI]

Damjan Kalajdzievski

Ximeng Mao

Pascal Fortier-Poisson

Guillaume Lajoie

Blake Aaron Richards

Trans. Mach. Learn. Res., 2023

Multi-view manifold learning of human brain-state trajectories.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Nat. Comput. Sci., 2023

How connectivity structure shapes rich and lazy learning in neural circuits.

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[DOI]

CoRR, 2023

Amortizing intractable inference in large language models.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency.

[BibT_eX]

[DOI]

CoRR, 2023

Delta-AI: Local objectives for amortized inference in sparse graphical models.

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[DOI]

CoRR, 2023

Discrete, compositional, and symbolic representations through attractor dynamics.

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[DOI]

CoRR, 2023

Synaptic Weight Distributions Depend on the Geometry of Plasticity.

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[DOI]

CoRR, 2023

Steerable Equivariant Representation Learning.

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[DOI]

CoRR, 2023

Sources of Richness and Ineffability for Phenomenally Conscious States.

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[DOI]

CoRR, 2023

Formalizing locality for normative synaptic plasticity models.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Unified, Scalable Framework for Neural Population Decoding.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flexible Phase Dynamics for Bio-Plausible Contrastive Learning.

[BibT_eX]

[DOI]

Ezekiel Williams

Colin Bredenberg

Guillaume Lajoie

Proceedings of the International Conference on Machine Learning, 2023

How gradient estimator variance and bias impact learning in neural networks.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reliability of CKA as a Similarity Measure in Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion.

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[DOI]

Nat. Mac. Intell., November, 2022

Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty.

[BibT_eX]

[DOI]

Thomas George

Guillaume Lajoie

Aristide Baratin

Trans. Mach. Learn. Res., 2022

Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost.

[BibT_eX]

[DOI]

Maximilian Puelma Touzel

Paul Cisek

Guillaume Lajoie

PLoS Comput. Biol., 2022

Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion.

[BibT_eX]

[DOI]

Nat. Mach. Intell., 2022

On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools.

[BibT_eX]

[DOI]

Ryan Vogt

Maximilian Puelma Touzel

Eli Shlizerman

Guillaume Lajoie

Frontiers Appl. Math. Stat., 2022

From Points to Functions: Infinite-dimensional Representations in Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2022

On Neural Architecture Inductive Biases for Relational Tasks.

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[DOI]

CoRR, 2022

Clarifying MCMC-based training of modern EBMs : Contrastive Divergence versus Maximum Likelihood.

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[DOI]

Léo Gagnon

Guillaume Lajoie

CoRR, 2022

Is a Modular Architecture Enough?

[BibT_eX]

[DOI]

Sarthak Mittal

Yoshua Bengio

Guillaume Lajoie

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Shared Neural Manifolds from Multi-Subject FMRI Data.

[BibT_eX]

[DOI]

Nicholas B. Turk-Browne

Smita Krishnaswamy

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Exploring the Geometry and Topology of Neural Network Loss Landscapes.

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[DOI]

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Multi-scale Feature Learning Dynamics: Insights for Double Descent.

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[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Compositional Attention: Disentangling Search and Retrieval.

[BibT_eX]

[DOI]

Sarthak Mittal

Sharath Chandra Raparthy

Irina Rish

Yoshua Bengio

Guillaume Lajoie

Proceedings of the Tenth International Conference on Learning Representations, 2022

Continuous-Time Meta-Learning with Forward Mode Differentiation.

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[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance.

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[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.

[BibT_eX]

[DOI]

Jean-Christophe Gagnon-Audet

Neural Comput., 2021

Learning function from structure in neuromorphic networks.

[BibT_eX]

[DOI]

Nat. Mach. Intell., 2021

Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance.

[BibT_eX]

[DOI]

CoRR, 2021

Efficient and robust multi-task learning in the brain with modular task primitives.

[BibT_eX]

[DOI]

Christian David Marton

Guillaume Lajoie

Kanaka Rajan

CoRR, 2021

Gradient Starvation: A Learning Proclivity in Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning.

[BibT_eX]

[DOI]

Danilo Jimenez Rezende

Michael Mozer

Yoshua Bengio

Chris Pal

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks.

[BibT_eX]

[DOI]

Olivier Tessier-Larivière

Luke Y. Prince

Pascal Fortier-Poisson

Proceedings of the 10th International IEEE/EMBS Conference on Neural Engineering, 2021

Implicit Regularization via Neural Feature Alignment.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

LEAD: Least-Action Dynamics for Min-Max Optimization.

[BibT_eX]

[DOI]

Reyhane Askari Hemmat

Amartya Mitra

Guillaume Lajoie

Ioannis Mitliagkas

CoRR, 2020

Implicit Regularization in Deep Learning: A View from Function Space.

[BibT_eX]

[DOI]

CoRR, 2020

Advantages of biologically-inspired adaptive neural activation in RNNs during learning.

[BibT_eX]

[DOI]

CoRR, 2020

Untangling tradeoffs between recurrence and self-attention in neural networks.

[BibT_eX]

[DOI]

CoRR, 2020

Internal representation dynamics and geometry in recurrent neural networks.

[BibT_eX]

[DOI]

Stefan Horoi

Guillaume Lajoie

Guy Wolf

CoRR, 2020

Untangling tradeoffs between recurrence and self-attention in artificial neural networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2020

2019

Dimensionality compression and expansion in Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics.

[BibT_eX]

[DOI]

Giancarlo Kerg

Kyle Goyette

Maximilian Puelma Touzel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2017

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2017

2016

Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems.

[BibT_eX]

[DOI]

Guillaume Lajoie

Kevin K. Lin

Jean-Philippe Thivierge

Eric Shea-Brown

PLoS Comput. Biol., 2016

Dynamic Signal Tracking in a Simple V1 Spiking Model.

[BibT_eX]

[DOI]

Guillaume Lajoie

Lai-Sang Young

Neural Comput., 2016

Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks.

[BibT_eX]

[DOI]

Philippe Vincent-Lamarre

Guillaume Lajoie

Jean-Philippe Thivierge

J. Comput. Neurosci., 2016

2014

Structured chaos shapes spike-response noise entropy in balanced neural networks.

[BibT_eX]

[DOI]

Guillaume Lajoie

Jean-Philippe Thivierge

Eric Shea-Brown

Frontiers Comput. Neurosci., 2014

2011

Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps.

[BibT_eX]

[DOI]

Guillaume Lajoie

Eric Shea-Brown

SIAM J. Appl. Dyn. Syst., 2011

Guillaume Lajoie

Timeline

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On csauthors.net:

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