| 2026 | EACL | Active Learning with Non-Uniform Costs for African Natural Language Processing. | Bonaventure F. P. Dossou, Ines Arous, Audrey Durand, Jackie Chi Kit Cheung |
| 2025 | AAAI | On Shallow Planning Under Partial Observability. | Randy Lefebvre, Audrey Durand |
| 2025 | LAK | Platform-based Adaptive Experimental Research in Education: Lessons Learned from The Digital Learning Challenge. | Ilya Musabirov, Mohi Reza, Haochen Song, Steven Moore, Pan Chen, Harsh Kumar, Tong Li, John C. Stamper, Norman L. Bier, Anna N. Rafferty, Thomas W. Price, Nina Deliu, Audrey Durand, Michael Liut, Joseph Jay Williams |
| 2024 | ICML | Randomized Confidence Bounds for Stochastic Partial Monitoring. | Maxime Heuillet, Ola Ahmad, Audrey Durand |
| 2024 | IDEAL | Association Rules Mining with Auto-encoders. | Thophile Berteloot, Richard Khoury, Audrey Durand |
| 2024 | UAI | Neural Active Learning Meets the Partial Monitoring Framework. | Maxime Heuillet, Ola Ahmad, Audrey Durand |
| 2023 | AAAI | Latent Space Evolution under Incremental Learning with Concept Drift (Student Abstract). | Charles Bourbeau, Audrey Durand |
| 2022 | AAAI | Annotation Cost-Sensitive Deep Active Learning with Limited Data (Student Abstract). | Renaud Bernatchez, Audrey Durand, Flavie Lavoie-Cardinal |
| 2022 | AAAI | A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning. | Mathieu Godbout, Maxime Heuillet, Sharath Chandra Raparthy, Rupali Bhati, Audrey Durand |
| 2022 | AI | Contextual bandit optimization of super-resolution microscopy. | Anthony Bilodeau, Renaud Bernatchez, Albert Michaud-Gagnon, Flavie Lavoie-Cardinal, Audrey Durand |
| 2020 | AAAI | Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract). | Qizhen Zhang, Audrey Durand, Joelle Pineau |
| 2020 | AISTATS | Old Dog Learns New Tricks: Randomized UCB for Bandit Problems. | Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton |
| 2020 | IJCAI | Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. | Maxime Wabartha, Audrey Durand, Vincent Franois-Lavet, Joelle Pineau |
| 2020 | LREC | A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well. | Nicolas Garneau, Mathieu Godbout, David Beauchemin, Audrey Durand, Luc Lamontagne |
| 2019 | AAAI | On-Line Adaptative Curriculum Learning for GANs. | Thang Doan, Joo Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm |
| 2019 | AAAI | Leveraging Observations in Bandits: Between Risks and Benefits. | Andrei Lupu, Audrey Durand, Doina Precup |
| 2019 | CoRL | Leveraging exploration in off-policy algorithms via normalizing flows. | Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm |
| 2018 | AAAI | Learning to Become an Expert: Deep Networks Applied to Super-Resolution Microscopy. | Louis-mile Robitaille, Audrey Durand, Marc-Andr Gardner, Christian Gagn, Paul De Koninck, Flavie Lavoie-Cardinal |
| 2018 | AAAI | Rating Super-Resolution Microscopy Images With Deep Learning. | Louis-mile Robitaille, Audrey Durand, Marc-Andr Gardner, Christian Gagn, Paul De Koninck, Flavie Lavoie-Cardinal |
| 2017 | IJCNN | Bayesian optimization for conditional hyperparameter spaces. | Julien-Charles Levesque, Audrey Durand, Christian Gagn, Robert Sabourin |
| 2012 | GECCO | Multi-objective evolutionary optimization for generating ensembles of classifiers in the ROC space. | Julien-Charles Levesque, Audrey Durand, Christian Gagn, Robert Sabourin |