| 2018 |
Prédiction et génération de données structurées à l'aide de réseaux de neurones et de décisions discrètes |
Dutil, Francis |
Bengio, Yoshua |
| 2023 |
Towards an extension of causal discovery with generative flow networks to latent variables models |
Manta, Dragos Cristian |
Bengio, Yoshua |
| 2025 |
Designing scalable and efficient neural networks |
Feng, Leo |
Bengio, Yoshua |
| 2004 |
Méthodes à noyaux appliquées à la gestion de portefeuille |
Dorion, Christian |
Bengio, Yoshua |
| 2010 |
Understanding deep architectures and the effect of unsupervised pre-training |
Erhan, Dumitru |
Bengio, Yoshua |
| 1999 |
Utilisation d'hyper-paramètres pour la sélection de variables |
Latendresse, Simon |
Bengio, Yoshua |
| 2024 |
Generative flow networks : theory and applications to structure learning |
Deleu, Tristan |
Bengio, Yoshua |
| 2022 |
Latent data augmentation and modular structure for improved generalization |
Lamb, Alexander |
Bengio, Yoshua |
| 2024 |
Deep learning applications to climate change mitigation |
Schmidt, Victor |
Bengio, Yoshua |
| 2009 |
Échantillonnage dynamique de champs markoviens |
Breuleux, Olivier |
Bengio, Yoshua |
| 2015 |
Advances in scaling deep learning algorithms |
Dauphin, Yann |
Bengio, Yoshua |
| 2018 |
Representation Learning for Visual Data |
Dumoulin, Vincent |
Bengio, Yoshua; Courville, Aaron |
| 2014 |
Deep learning of representations and its application to computer vision |
Goodfellow, Ian |
Bengio, Yoshua; Courville, Aaron |
| 2014 |
Distributed conditional computation |
Léonard, Nicholas |
Bengio, Yoshua; Courville, Aaron |
| 2017 |
Exploring Attention Based Model for Captioning Images |
Xu, Kelvin |
Bengio, Yoshua; Courville, Aaron |
| 2014 |
Leveraging noisy side information for disentangling of factors of variation in a supervised setting |
Carrier, Pierre Luc |
Bengio, Yoshua; Courville, Aaron |
| 2017 |
Learning visual representations with neural networks for video captioning and image generation |
Yao, Li |
Bengio, Yoshua; Courville, Aaron |
| 2013 |
Improving sampling, optimization and feature extraction in Boltzmann machines |
Desjardins, Guillaume |
Bengio, Yoshua; Courville, Aaron |
| 2025 |
Learning generative models from a control perspective |
Zhang, Dinghuai |
Bengio, Yoshua; Courville, Aaron |
| 2016 |
Sequential modeling, generative recurrent neural networks, and their applications to audio |
Mehri, Soroush |
Bengio, Yoshua; Courville, Aaron |
| 2020 |
Méta-enseignement : génération active d’exemples par apprentissage par renforcement |
Larocque, Stéphanie |
Bengio, Yoshua; Frejinger, Emma |
| 2000 |
Architecture et programme d'entraînement pour agents qui apprennent par renforcement |
Desaulniers, Julien |
Bengio, Yoshua; Gendreau, Michel |
| 2025 |
Evaluating and improving mathematical reasoning in large language models via skill combinations |
Shah, Vedant |
Bengio, Yoshua; Goyal, Anirudh |
| 2021 |
Locality and compositionality in representation learning for complex visual tasks |
Sylvain, Tristan |
Bengio, Yoshua; Hjelm, Rex Devon |
| 2009 |
Modèle informatique du coapprentissage des ganglions de la base et du cortex :
l'apprentissage par renforcement et le développement de représentations |
Rivest, François |
Bengio, Yoshua; Kalaska, John Francis |
| 2004 |
Réduction de dimension pour modèles graphiques probabilistes appliqués à la désambiguïsation sémantique |
Boisvert, Maryse |
Bengio, Yoshua; Kegl, Balazs |
| 2020 |
Towards better understanding and improving optimization in recurrent neural networks |
Kanuparthi, Bhargav |
Bengio, Yoshua; Lajoie, Guillaume |
| 2003 |
Quelques modèles de langage statistiques et graphiques lissés avec WordNet |
Jauvin, Christian |
Bengio, Yoshua; Langlais, Philippe |
| 2019 |
On challenges in training recurrent neural networks |
Anbil Parthipan, Sarath Chandar |
Bengio, Yoshua; Larochelle, Hugo |
| 2026 |
Applications of machine learning for biodiversity monitoring |
Teng, Mélisande |
Bengio, Yoshua; Larochelle, Hugo; Rolnick, David |
| 2019 |
Natural image processing and synthesis using deep learning |
Ganin, Iaroslav |
Bengio, Yoshua; Lempitsky, Victor |
| 2023 |
Learning and planning with noise in optimization and reinforcement learning |
Thomas, Valentin |
Bengio, Yoshua; Le Roux, Nicolas |
| 2016 |
Structured prediction and generative modeling using neural networks |
Kastner, Kyle |
Bengio, Yoshua; Memisevic, Roland |
| 2016 |
Designing Regularizers and Architectures for Recurrent Neural Networks |
Krueger, David |
Bengio, Yoshua; Memisevic, Roland |
| 2014 |
Modeling High-Dimensional Audio Sequences with Recurrent Neural Networks |
Boulanger-Lewandowski, Nicolas |
Bengio, Yoshua; Vincent, Pascal |
| 2024 |
Intrinsic exploration for reinforcement learning beyond rewards |
Creus-Castanyer, Roger |
Berseth, Glen |
| 2023 |
Deep learning on signals : discretization invariance, lossless compression and nonuniform compression |
Demeule, Léa |
Berseth, Glen |
| 2025 |
Inferring 2D and 3D character animation from sketches |
Brodt, Kirill |
Bessmeltsev, Mikhail |
| 2025 |
Interpreting and generating drawings via learning, geometry processing, and optimization |
Puhachov, Ivan |
Bessmeltsev, Mikhail |
| 2022 |
Stability-aware simplification of curve networks |
Neveu, William |
Bessmeltsev, Mikhail |