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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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2024 HarmonyCo : développement d'une bibliothèque Python pour le calcul optimisé de la médiane de permutations
2024 Deep learning applications to climate change mitigation
2024 Towards efficient and effective preference alignment for large language models
2024 Génération de données synthétiques pour l'adaptation hors-domaine non-supervisée en réponse aux questions : méthodes basées sur des règles contre réseaux de neurones
2024 Promoting robustness and compositionality in machine learning with insights from cognitive bottlenecks
2024 Towards maintainable machine learning development through continual and modular learning
2024 Towards human-AI co-creation for Hindustani music : modeling and interaction
2024 Exploring multivariate adaptations of the Lag-Llama univariate time series forecasting approach
2024 Domain adaptation in reinforcement learning via causal representation learning
2024 Mobility anomaly detection with intelligent video surveillance
2024 Leveraging foundation models towards semantic world representations for robotics
2024 Strategic planning of intracity electric vehicle charging station locations with integrated advanced demand dynamics
2024 Understanding our 3D world via generative modeling
2024 An investigation of weight perturbation for mitigating Spurious Correlations
2024 Constrained optimization for machine learning : algorithms and applications
2024 Modelling and evolving design-time uncertainty
2024 Learning optimizers for communication-efficient distributed learning
2024 Towards systematic generalization through meta-learning modular architectures and improving generative flow networks
2024 The role of continual learning and adaptive computation in improving computational efficiency of deep learning
2024 Generative models, theory and applications