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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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2023-10 Parameter-efficient modeling and robust automatic evaluation of image captioning
2023-11 Neurobiologically-inspired models : exploring behaviour prediction, learning algorithms, and reinforcement learning
2023-11 Small batch deep reinforcement learning
2023-11 Fairness through domain awareness : mitigating popularity bias for music discovery
2023-11 Domain-specific differencing and merging of models
2023-11 Building sample-efficient reinforcement learning
2023-11 Fair vaccination strategies with influence maximization : a case study on COVID-19
2023-12 Traitement automatique du langage naturel pour les textes juridiques : prédiction de verdict et exploitation de connaissances du domaine
2023-12 Towards an extension of causal discovery with generative flow networks to latent variables models
2023-12 Towards a unified model for speech and language processing
2023-12 Towards combining deep learning and statistical relational learning for reasoning on graphs
2023-12 Sketch-based interactive shape deformation using shading isophotes
2023-12 Methods for solving combinatorial pricing problems
2023-12 Apprentissage de descripteurs locaux pour l’amélioration des systèmes de SLAM visuel
2023-12 Detecting pre-error states and process deviations resulting from cognitive overload in aircraft pilots
2024-01 Beyond the horizon : improved long-range sequence modeling, from dynamical systems to language
2024-01 Dynamic capacities and priorities in stable matching
2024-01 The role of continual learning and adaptive computation in improving computational efficiency of deep learning
2024-02 Génération de données synthétiques pour l'adaptation hors-domaine non-supervisée en réponse aux questions : méthodes basées sur des règles contre réseaux de neurones
2024-02 Metaheuristics for vehicle routing problems : new methods and performance analysis