| 2025 | ICASSP | Easing Optimization Paths: a Circuit Perspective. | Ambroise Odonnat, Wassim Bouaziz, Vivien Cabannes |
| 2025 | ICLR | X-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. | Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun |
| 2024 | COLT | Mode Estimation with Partial Feedback. | Charles Arnal, Vivien Cabannes, Vianney Perchet |
| 2024 | ICASSP | Touring Sampling With Pushforward Maps. | Vivien Cabannes, Charles Arnal |
| 2024 | ICLR | Scaling Laws for Associative Memories. | Vivien Cabannes, Elvis Dohmatob, Alberto Bietti |
| 2024 | ICML | Learning Associative Memories with Gradient Descent. | Vivien Cabannes, Berfin Simsek, Alberto Bietti |
| 2023 | AISTATS | A Case of Exponential Convergence Rates for SVM. | Vivien Cabannes, Stefano Vigogna |
| 2023 | ICASSP | On Minimal Variations for Unsupervised Representation Learning. | Vivien Cabannes, Alberto Bietti, Randall Balestriero |
| 2023 | ICCV | Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. | Vivien Cabannes, Lon Bottou, Yann LeCun, Randall Balestriero |
| 2023 | ICML | The SSL Interplay: Augmentations, Inductive Bias, and Generalization. | Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti |
| 2020 | ICML | Structured Prediction with Partial Labelling through the Infimum Loss. | Vivien Cabannes, Alessandro Rudi, Francis R. Bach |