Guillaume Lajoie
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
24
Venues
6
Active years
2020–2025
Best venue rank
A*
Where they publish
Papers
24 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICASSP | Latent Representation Learning for Multimodal Brain Activity Translation. | Arman Afrasiyabi, Dhananjay Bhaskar, Erica L. Busch, Laurent Caplette, Rahul Singh, Guillaume Lajoie, Nicholas B. Turk-Browne, Smita Krishnaswamy |
| 2025 | ICLR | Accelerating Training with Neuron Interaction and Nowcasting Networks. | Boris Knyazev, Abhinav Moudgil, Guillaume Lajoie, Eugene Belilovsky, Simon Lacoste-Julien |
| 2025 | ICLR | Multi-agent cooperation through learning-aware policy gradients. | Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Agera y Arcas, Joo Sacramento |
| 2025 | ICLR | Expressivity of Neural Networks with Random Weights and Learned Biases. | Ezekiel Williams, Alexandre Payeur, Avery Hee-Woon Ryoo, Thomas Jiralerspong, Matthew G. Perich, Luca Mazzucato, Guillaume Lajoie |
| 2025 | ICML | Towards a Formal Theory of Representational Compositionality. | Eric Elmoznino, Thomas Jiralerspong, Yoshua Bengio, Guillaume Lajoie |
| 2025 | ICML | In-Context Learning and Occam's Razor. | Eric Elmoznino, Tom Marty, Tejas Kasetty, Lo Gagnon, Sarthak Mittal, Mahan Fathi, Dhanya Sridhar, Guillaume Lajoie |
| 2025 | ICML | Does learning the right latent variables necessarily improve in-context learning? | Sarthak Mittal, Eric Elmoznino, Lo Gagnon, Sangnie Bhardwaj, Guillaume Lajoie, Dhanya Sridhar |
| 2024 | ICLR | Delta-AI: Local objectives for amortized inference in sparse graphical models. | Jean-Pierre R. Falet, Hae Beom Lee, Nikolay Malkin, Chen Sun, Dragos Secrieru, Dinghuai Zhang, Guillaume Lajoie, Yoshua Bengio |
| 2024 | ICLR | Amortizing intractable inference in large language models. | Edward J. Hu, Moksh Jain, Eric Elmoznino, Younesse Kaddar, Guillaume Lajoie, Yoshua Bengio, Nikolay Malkin |
| 2024 | ICLR | Sufficient conditions for offline reactivation in recurrent neural networks. | Nanda H. Krishna, Colin Bredenberg, Daniel Levenstein, Blake Aaron Richards, Guillaume Lajoie |
| 2024 | ICLR | 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 |
| 2024 | ICLR | How connectivity structure shapes rich and lazy learning in neural circuits. | Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie |
| 2024 | ICLR | Synaptic Weight Distributions Depend on the Geometry of Plasticity. | Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards |
| 2023 | ICLR | Reliability of CKA as a Similarity Measure in Deep Learning. | MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie, Guy Wolf, Eugene Belilovsky |
| 2023 | ICLR | How gradient estimator variance and bias impact learning in neural networks. | Arna Ghosh, Yuhan Helena Liu, Guillaume Lajoie, Konrad P. Krding, Blake Aaron Richards |
| 2023 | ICML | Flexible Phase Dynamics for Bio-Plausible Contrastive Learning. | Ezekiel Williams, Colin Bredenberg, Guillaume Lajoie |
| 2022 | ICASSP | Embedding Signals on Graphs with Unbalanced Diffusion Earth Mover's Distance. | Alexander Tong, Guillaume Huguet, Dennis L. Shung, Amine Natik, Manik Kuchroo, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy |
| 2022 | ICLR | Continuous-Time Meta-Learning with Forward Mode Differentiation. | Tristan Deleu, David Kanaa, Leo Feng, Giancarlo Kerg, Yoshua Bengio, Guillaume Lajoie, Pierre-Luc Bacon |
| 2022 | ICLR | Compositional Attention: Disentangling Search and Retrieval. | Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie |
| 2022 | ICML | Multi-scale Feature Learning Dynamics: Insights for Double Descent. | Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie |
| 2022 | IDA | Exploring the Geometry and Topology of Neural Network Loss Landscapes. | Stefan Horoi, Jessie Huang, Bastian Rieck, Guillaume Lajoie, Guy Wolf, Smita Krishnaswamy |
| 2021 | AISTATS | Implicit Regularization via Neural Feature Alignment. | Aristide Baratin, Thomas George, Csar Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien |
| 2020 | AI | Low-Dimensional Dynamics of Encoding and Learning in Recurrent Neural Networks. | Stefan Horoi, Victor Geadah, Guy Wolf, Guillaume Lajoie |
| 2020 | ICML | Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. | Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio |