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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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Date Sort by date in descending order Title Sort by title in descending order
1992 Contribution à l'analyse des séries chronologiques multivariées
1986 Étude des autocovariances et des autocorrélations échantillonnales de modèles saisonniers
1993 Tests d'indépendance de deux séries chronologiques multivariées
1985 Le problème du choix de la séquence de classification des trains dans une gare de triage
2025 AI in climate change adaptation : applications to remote sensing and climate science
2022 Parametric Scattering Networks
2023 Neurobiologically-inspired models : exploring behaviour prediction, learning algorithms, and reinforcement learning
2022 Generalization in federated learning
2023 Sur l’application de la structure de graphes pour le calcul automatique de nombres de reproduction dans les modèles à compartiments déterministes
2024 Advancing adversarial robustness with feature desensitization and synthesized data
2024 Towards efficient large language models : training low-bitwidth variants and low-rank decomposition of pretrained models
2022 Agent abstraction in multi-agent reinforcement learning
2022 Problem hierarchies in continual learning
2025 Learning under constraints
2025 Design and implementation of an AI-Driven educating bot for personalized science education in middle school students
2023 Rethinking continual learning approach and study out-of-distribution generalization algorithms
2023 Predicting stock market trends using time-series classification with dynamic neural networks
2022 Improving information subsampling with local inhibition
2024 Exploring multivariate adaptations of the Lag-Llama univariate time series forecasting approach
2022 (Out-of-distribution?) : generalization in deep learning
2022 Renormalization group theory, scaling laws and deep learning
2023 On impact of mixing times in continual reinforcement learning
2021 Towards causal federated learning : a federated approach to learning representations using causal invariance
2023 Toward causal representation and structure learning
2023 Towards a unified model for speech and language processing
2025 A study of the role of entanglement in quantum kernel models
2020 Estimating the probability of a fleet vehicle accident : a deep learning approach using conditional variational auto-encoders
2022 Adaptive learning of tensor network structures
2022 On the VC-dimension of Tensor Networks
2025 Connecting neural networks, automata theory and tensor network methods for sequence data learning
Number of results : 1601