Guillaume Lajoie

111 papers A* 26A 1B 1Misc 2Journal 77Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Compression Perspective on Simplicity Bias. CoRR Tom Marty, Eric Elmoznino, Léo Gagnon, Tejas Kasetty, Mizu Nishikawa-Toomey, Sarthak Mittal, Guillaume Lajoie, Dhanya Sridhar
2026	J	`jnl`	JEDI: Jointly Embedded Inference of Neural Dynamics. CoRR Anirudh Jamkhandi, Ali Korojy, Olivier Codol, Guillaume Lajoie, Matthew G. Perich
2025	A*	`conf`	Accelerating Training with Neuron Interaction and Nowcasting Networks. ICLR Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien
2025	J	`jnl`	Amortized In-Context Bayesian Posterior Estimation. CoRR Sarthak Mittal, Niels Bracher, Guillaume Lajoie, Priyank Jaini, Marcus A. Brubaker
2025	J	`jnl`	Bidirectional Information Flow (BIF) - A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization. CoRR Juan David Guerra, Thomas Garbay, Guillaume Lajoie, Marco Bonizzato
2025	J	`jnl`	Celo: Training Versatile Learned Optimizers on a Compute Diet. Trans. Mach. Learn. Res. Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky
2025	A*	`conf`	Does learning the right latent variables necessarily improve in-context learning? ICML Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar
2025	J	`jnl`	Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning. CoRR Alexander Meulemans, Rajai Nasser, Maciej Wolczyk, Marissa A. Weis, Seijin Kobayashi, Blake A. Richards, Guillaume Lajoie, Angelika Steger, Marcus Hutter, James Manyika, Rif A. Saurous, João Sacramento, Blaise Agüera y Arcas
2025	J	`jnl`	Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning. CoRR Seijin Kobayashi, Yanick Schimpf, Maximilian Schlegel, Angelika Steger, Maciej Wolczyk, Johannes von Oswald, Nino Scherrer, Kaitlin Maile, Guillaume Lajoie, Blake A. Richards, Rif A. Saurous, James Manyika, Blaise Agüera y Arcas, Alexander Meulemans, João Sacramento
2025	A*	`conf`	Expressivity of Neural Networks with Random Weights and Learned Biases. ICLR Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G. Perich, Luca Mazzucato, Guillaume Lajoie
2025	J	`jnl`	Generalizable, real-time neural decoding with hybrid state-space models. CoRR Avery Hee-Woon Ryoo, Nanda H. Krishna, Ximeng Mao, Mehdi Azabou, Eva L. Dyer, Matthew G. Perich, Guillaume Lajoie
2025	A*	`conf`	In-Context Learning and Occam's Razor. ICML Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie
2025	J	`jnl`	In-Context Parametric Inference: Point or Distribution Estimators? CoRR Sarthak Mittal, Yoshua Bengio, Nikolay Malkin, Guillaume Lajoie
2025	J	`jnl`	Iterative Amortized Inference: Unifying In-Context Learning and Learned Optimizers. CoRR Sarthak Mittal, Divyat Mahajan, Guillaume Lajoie, Mohammad Pezeshki
2025	Misc	`conf`	Latent Representation Learning for Multimodal Brain Activity Translation. ICASSP Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy
2025	J	`jnl`	Learning Versatile Optimizers on a Compute Diet. CoRR Abhinav Moudgil, Boris Knyazev, Guillaume Lajoie, Eugene Belilovsky
2025	J	`jnl`	MesaNet: Sequence Modeling by Locally Optimal Test-Time Training. CoRR Johannes von Oswald, Nino Scherrer, Seijin Kobayashi, Luca Versari, Songlin Yang, Maximilian Schlegel, Kaitlin Maile, Yanick Schimpf, Oliver Sieberling, Alexander Meulemans, Rif A. Saurous, Guillaume Lajoie, Charlotte Frenkel, Razvan Pascanu, Blaise Agüera y Arcas, João Sacramento
2025	A*	`conf`	Multi-agent cooperation through learning-aware policy gradients. ICLR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2025	J	`jnl`	Next-Token Prediction Should be Ambiguity-Sensitive: A Meta-Learning Perspective. CoRR Léo Gagnon, Eric Elmoznino, Sarthak Mittal, Tom Marty, Tejas Kasetty, Dhanya Sridhar, Guillaume Lajoie
2025	J	`jnl`	Recursive Self-Aggregation Unlocks Deep Thinking in Large Language Models. CoRR Siddarth Venkatraman, Vineet Jain, Sarthak Mittal, Vedant Shah, Johan S. Obando-Ceron, Yoshua Bengio, Brian R. Bartoldson, Bhavya Kailkhura, Guillaume Lajoie, Glen Berseth, Nikolay Malkin, Moksh Jain
2025	J	`jnl`	Robust prior-biased acquisition function for human-in-the-loop Bayesian optimization. Knowl. Based Syst. Rose Guay-Hottin, Lison Kardassevitch, Hugo Pham, Guillaume Lajoie, Marco Bonizzato
2025	J	`jnl`	Sufficient conditions for offline reactivation in recurrent neural networks. CoRR Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein, Blake A. Richards, Guillaume Lajoie
2025	A*	`conf`	Towards a Formal Theory of Representational Compositionality. ICML Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie
2025	J	`jnl`	Tracing the Representation Geometry of Language Models from Pretraining to Post-training. CoRR Melody Zixuan Li, Kumar Krishna Agrawal, Arna Ghosh, Komal Kumar Teru, Adam Santoro, Guillaume Lajoie, Blake A. Richards
2024	J	`jnl`	A Complexity-Based Theory of Compositionality. CoRR Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie
2024	J	`jnl`	Accelerating Training with Neuron Interaction and Nowcasting Networks. CoRR Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien
2024	A*	`conf`	Amortizing intractable inference in large language models. ICLR Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
2024	A*	`conf`	Delta-AI: Local objectives for amortized inference in sparse graphical models. ICLR Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
2024	J	`jnl`	Does learning the right latent variables necessarily improve in-context learning? CoRR Sarthak Mittal, Eric Elmoznino, Léo Gagnon, Sangnie Bhardwaj, Dhanya Sridhar, Guillaume Lajoie
2024	J	`jnl`	Expressivity of Neural Networks with Random Weights and Learned Biases. CoRR Ezekiel Williams, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Alexandre Payeur, Matthew G. Perich, Luca Mazzucato, Guillaume Lajoie
2024	A*	`conf`	How connectivity structure shapes rich and lazy learning in neural circuits. ICLR Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
2024	J	`jnl`	In-context learning and Occam's razor. CoRR Eric Elmoznino, Tom Marty, Tejas Kasetty, Léo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie
2024	J	`jnl`	Latent Representation Learning for Multimodal Brain Activity Translation. CoRR Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy
2024	A*	`conf`	Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. ICLR Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan
2024	J	`jnl`	Multi-agent cooperation through learning-aware policy gradients. CoRR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake A. Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2024	J	`jnl`	Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization. PLoS Comput. Biol. Victor Geadah, Stefan Horoi, Giancarlo Kerg, Guy Wolf, Guillaume Lajoie
2024	A*	`conf`	Sufficient conditions for offline reactivation in recurrent neural networks. ICLR Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie
2024	A*	`conf`	Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards
2024	J	`jnl`	When can transformers compositionally generalize in-context? CoRR Seijin Kobayashi, Simon Schug, Yassir Akram, Florian Redhardt, Johannes von Oswald, Razvan Pascanu, Guillaume Lajoie, João Sacramento
2023	A*	`conf`	A Unified, Scalable Framework for Neural Population Decoding. NeurIPS Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
2023	J	`jnl`	A Unified, Scalable Framework for Neural Population Decoding. CoRR Mehdi Azabou, Vinam Arora, Venkataramana Ganesh, Ximeng Mao, Santosh Nachimuthu, Michael J. Mendelson, Blake A. Richards, Matthew G. Perich, Guillaume Lajoie, Eva L. Dyer
2023	J	`jnl`	Amortizing intractable inference in large language models. CoRR Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin
2023	J	`jnl`	Delta-AI: Local objectives for amortized inference in sparse graphical models. CoRR Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio
2023	J	`jnl`	Discrete, compositional, and symbolic representations through attractor dynamics. CoRR Andrew Nam, Eric Elmoznino, Nikolay Malkin, Chen Sun, Yoshua Bengio, Guillaume Lajoie
2023	A*	`conf`	Flexible Phase Dynamics for Bio-Plausible Contrastive Learning. ICML Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie
2023	J	`jnl`	Flexible Phase Dynamics for Bio-Plausible Contrastive Learning. CoRR Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie
2023	A*	`conf`	Formalizing locality for normative synaptic plasticity models. NeurIPS Colin Bredenberg, Ezekiel Williams, Cristina Savin, Blake A. Richards, Guillaume Lajoie
2023	J	`jnl`	How connectivity structure shapes rich and lazy learning in neural circuits. CoRR Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
2023	A*	`conf`	How gradient estimator variance and bias impact learning in neural networks. ICLR Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad P. Körding, Blake Aaron Richards
2023	J	`jnl`	LEAD: Min-Max Optimization from a Physical Perspective. Trans. Mach. Learn. Res. Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas
2023	J	`jnl`	Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. CoRR Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan
2023	J	`jnl`	Multi-view manifold learning of human brain-state trajectories. Nat. Comput. Sci. Erica L. Busch, Jessie Huang, Andrew Benz, Tom Wallenstein, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy, Nicholas B. Turk-Browne
2023	A*	`conf`	Reliability of CKA as a Similarity Measure in Deep Learning. ICLR MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
2023	J	`jnl`	Sources of Richness and Ineffability for Phenomenally Conscious States. CoRR Xu Ji, Eric Elmoznino, George Deane, Axel Constant, Guillaume Dumas, Guillaume Lajoie, Jonathan Simon, Yoshua Bengio
2023	J	`jnl`	Steerable Equivariant Representation Learning. CoRR Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan
2023	J	`jnl`	Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards
2023	J	`jnl`	Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. Trans. Mach. Learn. Res. Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake Aaron Richards
2022	J	`jnl`	Author Correction: Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mac. Intell. Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2022	A*	`conf`	Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. NeurIPS Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
2022	J	`jnl`	Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules. CoRR Yuhan Helena Liu, Arna Ghosh, Blake A. Richards, Eric Shea-Brown, Guillaume Lajoie
2022	J	`jnl`	Clarifying MCMC-based training of modern EBMs : Contrastive Divergence versus Maximum Likelihood. CoRR Léo Gagnon, Guillaume Lajoie
2022	A*	`conf`	Compositional Attention: Disentangling Search and Retrieval. ICLR Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
2022	A*	`conf`	Continuous-Time Meta-Learning with Forward Mode Differentiation. ICLR Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon
2022	J	`jnl`	Continuous-Time Meta-Learning with Forward Mode Differentiation. CoRR Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon
2022	Misc	`conf`	Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. ICASSP Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	B	`conf`	Exploring the Geometry and Topology of Neural Network Loss Landscapes. IDA Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2022	J	`jnl`	From Points to Functions: Infinite-dimensional Representations in Diffusion Models. CoRR Sarthak Mittal, Guillaume Lajoie, Stefan Bauer, Arash Mehrjou
2022	J	`jnl`	Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. Nat. Mach. Intell. Matthew Farrell, Stefano Recanatesi, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2022	A*	`conf`	Is a Modular Architecture Enough? NeurIPS Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
2022	J	`jnl`	Is a Modular Architecture Enough? CoRR Sarthak Mittal, Yoshua Bengio, Guillaume Lajoie
2022	J	`jnl`	Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. CoRR Thomas George, Guillaume Lajoie, Aristide Baratin
2022	J	`jnl`	Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. Trans. Mach. Learn. Res. Thomas George, Guillaume Lajoie, Aristide Baratin
2022	—	`conf`	Learning Shared Neural Manifolds from Multi-Subject FMRI Data. MLSP Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2022	J	`jnl`	Learning shared neural manifolds from multi-subject FMRI data. CoRR Jessie Huang, Erica L. Busch, Tom Wallenstein, Michal Gerasimiuk, Andrew Benz, Guillaume Lajoie, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy
2022	A*	`conf`	Multi-scale Feature Learning Dynamics: Insights for Double Descent. ICML Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
2022	J	`jnl`	On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. Frontiers Appl. Math. Stat. Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie
2022	J	`jnl`	On Neural Architecture Inductive Biases for Relational Tasks. CoRR Giancarlo Kerg, Sarthak Mittal, David Rolnick, Yoshua Bengio, Blake A. Richards, Guillaume Lajoie
2022	J	`jnl`	Performance-gated deliberation: A context-adapted strategy in which urgency is opportunity cost. PLoS Comput. Biol. Maximilian Puelma Touzel, Paul Cisek, Guillaume Lajoie
2022	J	`jnl`	Reliability of CKA as a Similarity Measure in Deep Learning. CoRR MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky
2022	J	`jnl`	Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer. CoRR Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake A. Richards
2021	J	`jnl`	Compositional Attention: Disentangling Search and Retrieval. CoRR Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
2021	J	`jnl`	Efficient and robust multi-task learning in the brain with modular task primitives. CoRR Christian David Marton, Guillaume Lajoie, Kanaka Rajan
2021	J	`jnl`	Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance. CoRR Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy
2021	A*	`conf`	Gradient Starvation: A Learning Proclivity in Neural Networks. NeurIPS Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
2021	A	`conf`	Implicit Regularization via Neural Feature Alignment. AISTATS Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2021	J	`jnl`	Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. Germán 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
2021	J	`jnl`	Learning function from structure in neuromorphic networks. Nat. Mach. Intell. Laura E. Suárez, Blake A. Richards, Guillaume Lajoie, Bratislav Misic
2021	J	`jnl`	Multi-scale Feature Learning Dynamics: Insights for Double Descent. CoRR Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
2021	—	`conf`	PNS-GAN: Conditional Generation of Peripheral Nerve Signals in the Wavelet Domain via Adversarial Networks. NER Olivier Tessier-Larivière, Luke Y. Prince, Pascal Fortier-Poisson, Lorenz Wernisch, Oliver Armitage, Emil Hewage, Guillaume Lajoie, Blake A. Richards
2021	—	`conf`	Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
2021	J	`jnl`	Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
2020	J	`jnl`	Advantages of biologically-inspired adaptive neural activation in RNNs during learning. CoRR Victor Geadah, Giancarlo Kerg, Stefan Horoi, Guy Wolf, Guillaume Lajoie
2020	J	`jnl`	Gradient Starvation: A Learning Proclivity in Neural Networks. CoRR Mohammad Pezeshki, Sékou-Oumar Kaba, Yoshua Bengio, Aaron C. Courville, Doina Precup, Guillaume Lajoie
2020	J	`jnl`	Implicit Regularization in Deep Learning: A View from Function Space. CoRR Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
2020	J	`jnl`	Internal representation dynamics and geometry in recurrent neural networks. CoRR Stefan Horoi, Guillaume Lajoie, Guy Wolf
2020	J	`jnl`	LEAD: Least-Action Dynamics for Min-Max Optimization. CoRR Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas
2020	A*	`conf`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	J	`jnl`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	—	`conf`	Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. Canadian AI Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie
2020	J	`jnl`	On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. CoRR Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman, Guillaume Lajoie
2020	A*	`conf`	Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
2020	J	`jnl`	Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
2019	J	`jnl`	Dimensionality compression and expansion in Deep Neural Networks. CoRR Stefano Recanatesi, Matthew Farrell, Madhu Advani, Timothy Moore, Guillaume Lajoie, Eric Shea-Brown
2019	A*	`conf`	Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie
2019	J	`jnl`	Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie
2017	J	`jnl`	Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface. PLoS Comput. Biol. Guillaume Lajoie, Nedialko I. Krouchev, John F. Kalaska, Adrienne L. Fairhall, Eberhard E. Fetz
2016	J	`jnl`	Driving reservoir models with oscillations: a solution to the extreme structural sensitivity of chaotic networks. J. Comput. Neurosci. Philippe Vincent-Lamarre, Guillaume Lajoie, Jean-Philippe Thivierge
2016	J	`jnl`	Dynamic Signal Tracking in a Simple V1 Spiking Model. Neural Comput. Guillaume Lajoie, Lai-Sang Young
2016	J	`jnl`	Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems. PLoS Comput. Biol. Guillaume Lajoie, Kevin K. Lin, Jean-Philippe Thivierge, Eric Shea-Brown
2014	J	`jnl`	Structured chaos shapes spike-response noise entropy in balanced neural networks. Frontiers Comput. Neurosci. Guillaume Lajoie, Jean-Philippe Thivierge, Eric Shea-Brown
2011	J	`jnl`	Shared Inputs, Entrainment, and Desynchrony in Elliptic Bursters: From Slow Passage to Discontinuous Circle Maps. SIAM J. Appl. Dyn. Syst. Guillaume Lajoie, Eric Shea-Brown