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Thèses et mémoires

Des thèses et mémoires de nos étudiants sont conservés et consultables dans Papyrus, le dépôt institutionnel de l'Université de Montréal.

 

 

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2018-12 Advances in deep learning with limited supervision and computational resources
2020-08 On improving variational inference with low-variance multi-sample estimators
2020-09 Estimation neuronale de l'information mutuelle
2019-12 Emerging communication between competitive agents
2020-03 Deep learning and reinforcement learning methods for grounded goal-oriented dialogue
2024-06 Promoting robustness and compositionality in machine learning with insights from cognitive bottlenecks
2019-12 Representation learning in unsupervised domain translation
2018-04 Sequence to sequence learning and its speech applications
2017-08 Generative models for natural images
2018-08 Latent variable language models
2023-10 Probability flows in deep learning
2016-08 Influencing the Properties of Latent Spaces
2023-08 Sequential decision modeling in uncertain conditions
2024-03 Self-supervision for reinforcement learning
2023-05 Emergence of language-like latents in deep neural networks
2023-08 Coordination in generative modeling, automatic differentiation and multi-agent learning
2023-08 Improving predictive behavior under distributional shift
2023-07 Differentiable best response shaping
2002 Modèle d'équilibre dans les réseaux de transport en commun : le cas des capacités explicites des services
1993 Évaluation du potentiel d'un modèle connexionniste pour la classification de textures échographiques médicales