Theses
PhD thesis
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New Faithfulness-Centric Interpretability Paradigms for Natural Language Processing
by Andreas Madsen, with Siva Reddy and Sarath Chandar as supervisors.
Polytechnique Montreal ⸺ November 2024.
[thesis]
Master's thesis
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Training Neural Networks to Perform Structured Prediction Task
by Maziar Sargordi, with Sarath Chandar and Amal Zouaq as supervisors.
Polytechnique Montréal ⸺ August 2024.
[thesis] -
The Role of Continual Learning and Adaptive Computation in Improving Computational Efficiency of Deep Learning
by Kshitij Gupta, with Irina Rish and Sarath Chandar as supervisors.
Université de Montréal ⸺ January 2024.
[thesis] -
Towards Adaptive Deep Model-Based Reinforcement Learning
by Ali Rahimi-Kalahroudi, with Sarath Chandar as supervisor.
Université de Montréal ⸺ November 2023.
[thesis] -
Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints
by Daphné Lafleur, with Gilles Pesant and Sarath Chandar as supervisors.
Polytechnique Montréal ⸺ November 2022.
[thesis] -
Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics
by Charan Reddy, with Sarath Chandar as supervisor.
Université de Montréal ⸺ July 2022.
[thesis] -
TAG: Task-based Accumulated Gradients for Lifelong learning
by Pranshu Malviya, with Balaraman Ravindran and Sarath Chandar as supervisors.
Indian Institute of Technology, Madras ⸺ January 2022.
[thesis] -
PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks
by Mojtaba Faramarzi, with Sarath Chandar as supervisor.
Université de Montréal ⸺ October 2021.
[thesis] -
IIRC: Incremental Implicitly-Refined Classification
by Mohamed Abdelsalam, with Sarath Chandar as supervisor.
Université de Montréal ⸺ May 2021.
[thesis] -
Continuous Coordination As a Realistic Scenario for Lifelong Learning
by Akilesh Badrinaaraayanan, with Aaron Courville and Sarath Chandar as supervisors.
Université de Montréal ⸺ April 2021.
[thesis]