Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning. - Maxime Latulippe; Alexandre Drouin; Philippe Giguère; François Laviolette (IJCAI, 2013)

Learning a peptide-protein binding affinity predictor with kernel ridge regression. - Sébastien Giguère; Mario Marchand; François Laviolette; Alexandre Drouin; Jacques Corbeil (BMC Bioinform., 2013)

Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine. - Alexandre Drouin; Sébastien Giguère; Vladana Sagatovich; Maxime Déraspe; François Laviolette; Mario Marchand; Jacques Corbeil (CoRR, 2014)

Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance. - Alexandre Drouin; Sébastien Giguère; Maxime Déraspe; François Laviolette; Mario Marchand; Jacques Corbeil (CoRR, 2015)

Large scale modeling of antimicrobial resistance with interpretable classifiers. - Alexandre Drouin; Frédéric Raymond; Gaël Letarte St-Pierre; Mario Marchand; Jacques Corbeil; François Laviolette (CoRR, 2016)

Maximum Margin Interval Trees. - Alexandre Drouin; Toby Hocking; François Laviolette (NIPS, 2017)

Deep Learning for Electromyographic Hand Gesture Signal Classification by Leveraging Transfer Learning. - Ulysse Côté Allard; Cheikh Latyr Fall; Alexandre Drouin; Alexandre Campeau-Lecours; Clément Gosselin; Kyrre Glette; François Laviolette; Benoit Gosselin (CoRR, 2018)

Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites. - Faizy Ahsan; Alexandre Drouin; François Laviolette; Doina Precup; Mathieu Blanchette (BIBM, 2020)

Embedding Propagation: Smoother Manifold for Few-Shot Classification. - Pau Rodríguez; Issam H. Laradji; Alexandre Drouin; Alexandre Lacoste (ECCV (26), 2020)

Differentiable Causal Discovery from Interventional Data. - Philippe Brouillard; Sébastien Lachapelle; Alexandre Lacoste; Simon Lacoste-Julien; Alexandre Drouin (NeurIPS, 2020)

In search of robust measures of generalization. - Gintare Karolina Dziugaite; Alexandre Drouin; Brady Neal; Nitarshan Rajkumar; Ethan Caballero; Linbo Wang 003; Ioannis Mitliagkas; Daniel M. Roy 001 (NeurIPS, 2020)

Synbols: Probing Learning Algorithms with Synthetic Datasets. - Alexandre Lacoste; Pau Rodríguez López; Frederic Branchaud-Charron; Parmida Atighehchian; Massimo Caccia; Issam Hadj Laradji; Alexandre Drouin; Matt Craddock; Laurent Charlin; David Vázquez 001 (NeurIPS, 2020)

byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings. - Xiang Zhang; Alexandre Drouin; Raymond Li (CoRR, 2021)

Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. - Alexandre Lacoste; Evan David Sherwin; Hannah Kerner; Hamed Alemohammad; Björn Lütjens; Jeremy Irvin; David Dao; Alex Chang; Mehmet Gunturkun; Alexandre Drouin; Pau Rodríguez; David Vázquez 001 (CoRR, 2021)

Typing assumptions improve identification in causal discovery. - Philippe Brouillard; Perouz Taslakian; Alexandre Lacoste; Sébastien Lachapelle; Alexandre Drouin (CLeaR, 2022)

TACTiS: Transformer-Attentional Copulas for Time Series. - Alexandre Drouin; Étienne Marcotte; Nicolas Chapados (ICML, 2022)

RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data. - Thibaud Godon; Pier-Luc Plante; Baptiste Bauvin; Elina Francovic-Fontaine; Alexandre Drouin; Jacques Corbeil (CoRR, 2022)

Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. - Étienne Marcotte; Valentina Zantedeschi; Alexandre Drouin; Nicolas Chapados (ICML, 2023)

GEO-Bench: Toward Foundation Models for Earth Monitoring. - Alexandre Lacoste; Nils Lehmann; Pau Rodríguez; Evan D. Sherwin; Hannah Kerner; Björn Lütjens; Jeremy Irvin; David Dao; Hamed Alemohammad; Alexandre Drouin; Mehmet Gunturkun; Gabriel Huang; et al. (NeurIPS, 2023)

Invariant Causal Set Covering Machines. - Thibaud Godon; Baptiste Bauvin; Pascal Germain; Jacques Corbeil; Alexandre Drouin (CoRR, 2023)

Causal Discovery with Language Models as Imperfect Experts. - Stephanie Long; Alexandre Piché; Valentina Zantedeschi; Tibor Schuster; Alexandre Drouin (CoRR, 2023)

Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. - Chris Chinenye Emezue; Alexandre Drouin; Tristan Deleu; Stefan Bauer; Yoshua Bengio (CoRR, 2023)

Lag-Llama: Towards Foundation Models for Time Series Forecasting. - Kashif Rasul; Arjun Ashok; Andrew Robert Williams; Arian Khorasani; George Adamopoulos; Rishika Bhagwatkar; Marin Bilos; Hena Ghonia; Nadhir Vincent Hassen; Anderson Schneider; Sahil Garg; Alexandre Drouin; et al. (CoRR, 2023)

Capture the Flag: Uncovering Data Insights with Large Language Models. - Issam H. Laradji; Perouz Taslakian; Sai Rajeswar; Valentina Zantedeschi; Alexandre Lacoste; Nicolas Chapados; David Vázquez 001; Christopher Pal; Alexandre Drouin (CoRR, 2023)

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. - Arjun Ashok; Étienne Marcotte; Valentina Zantedeschi; Nicolas Chapados; Alexandre Drouin (ICLR, 2024)

WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? - Alexandre Drouin; Maxime Gasse; Massimo Caccia; Issam H. Laradji; Manuel Del Verme; Tom Marty; David Vázquez 001; Nicolas Chapados; Alexandre Lacoste (ICML, 2024)

WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. - Léo Boisvert; Megh Thakkar; Maxime Gasse; Massimo Caccia; Thibault Le Sellier de Chezelles; Quentin Cappart; Nicolas Chapados; Alexandre Lacoste; Alexandre Drouin (NeurIPS, 2024)

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? - Alexandre Drouin; Maxime Gasse; Massimo Caccia; Issam H. Laradji; Manuel Del Verme; Tom Marty; Léo Boisvert; Megh Thakkar; Quentin Cappart; David Vázquez 001; Nicolas Chapados; Alexandre Lacoste (CoRR, 2024)

Evaluating Interventional Reasoning Capabilities of Large Language Models. - Tejas Kasetty; Divyat Mahajan; Gintare Karolina Dziugaite; Alexandre Drouin; Dhanya Sridhar (CoRR, 2024)

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. - Gaurav Sahu; Abhay Puri; Juan A. Rodríguez; Alexandre Drouin; Perouz Taslakian; Valentina Zantedeschi; Alexandre Lacoste; David Vázquez 001; Nicolas Chapados; Christopher Pal; Sai Rajeswar; Issam Hadj Laradji (CoRR, 2024)

Causal Representation Learning in Temporal Data via Single-Parent Decoding. - Philippe Brouillard; Sébastien Lachapelle; Julia Kaltenborn; Yaniv Gurwicz; Dhanya Sridhar; Alexandre Drouin; Peer Nowack; Jakob Runge; David Rolnick (CoRR, 2024)

Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning. - Benjamin Leblanc; Mathieu Bazinet; Nathaniel D'Amours; Alexandre Drouin; Pascal Germain (CoRR, 2024)

Context is Key: A Benchmark for Forecasting with Essential Textual Information. - Andrew Robert Williams; Arjun Ashok; Étienne Marcotte; Valentina Zantedeschi; Jithendaraa Subramanian; Roland Riachi; James Requeima; Alexandre Lacoste; Irina Rish; Nicolas Chapados; Alexandre Drouin (CoRR, 2024)

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications. - Philippe Brouillard; Chandler Squires; Jonas Wahl; Konrad P. Kording; Karen Sachs; Alexandre Drouin; Dhanya Sridhar (CoRR, 2024)

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications. - Philippe Brouillard; Chandler Squires; Jonas Wahl; Konrad K; Karen Sachs; Alexandre Drouin; Dhanya Sridhar (CLeaR, 2025)

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. - Gaurav Sahu; Abhay Puri; Juan A. Rodríguez; Amirhossein Abaskohi; Mohammad Chegini; Alexandre Drouin; Perouz Taslakian; Valentina Zantedeschi; Alexandre Lacoste; David Vázquez 001; Nicolas Chapados; Christopher Pal; et al. (ICLR, 2025)

The BrowserGym Ecosystem for Web Agent Research. - Thibault Le Sellier de Chezelles; Maxime Gasse; Alexandre Lacoste; Massimo Caccia; Alexandre Drouin; Léo Boisvert; Megh Thakkar; Tom Marty; Rim Assouel; Sahar Omidi Shayegan; Lawrence Keunho Jang; Xing Han Lù; et al. (Trans. Mach. Learn. Res., 2025)

Learning to Defer for Causal Discovery with Imperfect Experts. - Oscar Clivio; Divyat Mahajan; Perouz Taslakian; Sara Magliacane; Ioannis Mitliagkas; Valentina Zantedeschi; Alexandre Drouin (CoRR, 2025)

DoomArena: A framework for Testing AI Agents Against Evolving Security Threats. - Léo Boisvert; Mihir Bansal; Chandra Kiran Reddy Evuru; Gabriel Huang; Abhay Puri; Avinandan Bose; Maryam Fazel; Quentin Cappart; Jason Stanley; Alexandre Lacoste; Alexandre Drouin; Krishnamurthy Dvijotham (CoRR, 2025)

How to Train Your LLM Web Agent: A Statistical Diagnosis. - Dheeraj Vattikonda; Santhoshi Ravichandran; Emiliano Penaloza; Hadi Nekoei; Megh Thakkar; Thibault Le Sellier de Chezelles; Nicolas Gontier; Miguel Muñoz-Mármol; Sahar Omidi Shayegan; Stefania Raimondo; Xue Liu; Alexandre Drouin; et al. (CoRR, 2025)

Beyond Naïve Prompting: Strategies for Improved Zero-shot Context-aided Forecasting with LLMs. - Arjun Ashok; Andrew Robert Williams; Vincent Zhihao Zheng; Irina Rish; Nicolas Chapados; Étienne Marcotte; Valentina Zantedeschi; Alexandre Drouin (CoRR, 2025)