Predicting genre labels for artist using FreeDB. - James Bergstra; Alexandre Lacoste; Douglas Eck (ISMIR, 2006)

A Supervised Classification Algorithm for Note Onset Detection. - Alexandre Lacoste; Douglas Eck (EURASIP J. Adv. Signal Process., 2007)

A PAC-Bayes Sample-compression Approach to Kernel Methods. - Pascal Germain; Alexandre Lacoste; François Laviolette; Mario Marchand; Sara Shanian (ICML, 2011)

Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets. - Alexandre Lacoste; François Laviolette; Mario Marchand (AISTATS, 2012)

Agnostic Bayesian Learning of Ensembles. - Alexandre Lacoste; Mario Marchand; François Laviolette; Hugo Larochelle (ICML, 2014)

Sequential Model-Based Ensemble Optimization. - Alexandre Lacoste; Hugo Larochelle; Mario Marchand; François Laviolette (UAI, 2014)

WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. - Daniel Hewlett; Alexandre Lacoste; Llion Jones; Illia Polosukhin; Andrew Fandrianto; Jay Han; Matthew Kelcey; David Berthelot (ACL (1), 2016)

PAC-Bayesian Theory Meets Bayesian Inference. - Pascal Germain; Francis R. Bach; Alexandre Lacoste; Simon Lacoste-Julien (NIPS, 2016)

Hierarchical Question Answering for Long Documents. - Eunsol Choi; Daniel Hewlett; Alexandre Lacoste; Illia Polosukhin; Jakob Uszkoreit; Jonathan Berant (CoRR, 2016)

Coarse-to-Fine Question Answering for Long Documents. - Eunsol Choi; Daniel Hewlett; Jakob Uszkoreit; Illia Polosukhin; Alexandre Lacoste; Jonathan Berant (ACL (1), 2017)

Accurate Supervised and Semi-Supervised Machine Reading for Long Documents. - Izzeddin Gur; Daniel Hewlett; Alexandre Lacoste; Llion Jones (EMNLP, 2017)

Bayesian Hypernetworks. - David Krueger 001; Chin-Wei Huang; Riashat Islam; Ryan Turner; Alexandre Lacoste; Aaron C. Courville (CoRR, 2017)

Deep Prior. - Alexandre Lacoste; Thomas Boquet; Negar Rostamzadeh; Boris N. Oreshkin; Wonchang Chung; David Krueger 001 (CoRR, 2017)

Learning Heuristics for the TSP by Policy Gradient. - Michel Deudon; Pierre Cournut; Alexandre Lacoste; Yossiri Adulyasak; Louis-Martin Rousseau (CPAIOR, 2018)

Neural Autoregressive Flows. - Chin-Wei Huang; David Krueger 001; Alexandre Lacoste; Aaron C. Courville (ICML, 2018)

Improving Explorability in Variational Inference with Annealed Variational Objectives. - Chin-Wei Huang; Shawn Tan; Alexandre Lacoste; Aaron C. Courville (NeurIPS, 2018)

TADAM: Task dependent adaptive metric for improved few-shot learning. - Boris N. Oreshkin; Pau Rodríguez López; Alexandre Lacoste (NeurIPS, 2018)

Uncertainty in Multitask Transfer Learning. - Alexandre Lacoste; Boris N. Oreshkin; Wonchang Chung; Thomas Boquet; Negar Rostamzadeh; David Krueger 001 (CoRR, 2018)

Hierarchical Importance Weighted Autoencoders. - Chin-Wei Huang; Kris Sankaran; Eeshan Dhekane; Alexandre Lacoste; Aaron C. Courville (ICML, 2019)

Probability Distillation: A Caveat and Alternatives. - Chin-Wei Huang; Faruk Ahmed; Kundan Kumar; Alexandre Lacoste; Aaron C. Courville (UAI, 2019)

Adaptive Deep Kernel Learning. - Prudencio Tossou; Basile Dura; François Laviolette; Mario Marchand; Alexandre Lacoste (CoRR, 2019)

Quantifying the Carbon Emissions of Machine Learning. - Alexandre Lacoste; Alexandra Luccioni; Victor Schmidt; Thomas Dandres (CoRR, 2019)

Stochastic Neural Network with Kronecker Flow. - Chin-Wei Huang; Ahmed Touati; Pascal Vincent; Gintare Karolina Dziugaite; Alexandre Lacoste; Aaron C. Courville (AISTATS, 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)

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. - Massimo Caccia; Pau Rodríguez; Oleksiy Ostapenko; Fabrice Normandin; Min Lin; Lucas Page-Caccia; Issam Hadj Laradji; Irina Rish; Alexandre Lacoste; David Vázquez 001; Laurent Charlin (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)

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning. - Massimo Caccia; Pau Rodríguez; Oleksiy Ostapenko; Fabrice Normandin; Min Lin; Lucas Caccia; Issam H. Laradji; Irina Rish; Alexandre Lacoste; David Vázquez 001; Laurent Charlin (CoRR, 2020)

Bayesian active learning for production, a systematic study and a reusable library. - Parmida Atighehchian; Frédéric Branchaud-Charron; Alexandre Lacoste (CoRR, 2020)

Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery. - Issam H. Laradji; Pau Rodríguez; Freddie Kalaitzis; David Vázquez 001; Ross Young; Ed Davey; Alexandre Lacoste (CoRR, 2020)

Estimating Carbon Emissions of Artificial Intelligence [Opinion]. - Alexandra Luccioni; Alexandre Lacoste; Victor Schmidt (IEEE Technol. Soc. Mag., 2020)

Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data. - Oscar Mañas; Alexandre Lacoste; Xavier Giró-i-Nieto; David Vázquez 001; Pau Rodríguez (ICCV, 2021)

Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. - Pau Rodríguez; Massimo Caccia; Alexandre Lacoste; Lee Zamparo; Issam H. Laradji; Laurent Charlin; David Vázquez 001 (ICCV, 2021)

Can Active Learning Preemptively Mitigate Fairness Issues? - Frédéric Branchaud-Charron; Parmida Atighehchian; Pau Rodríguez; Grace Abuhamad; Alexandre Lacoste (CoRR, 2021)

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. - Yashas Annadani; Jonas Rothfuss; Alexandre Lacoste; Nino Scherrer; Anirudh Goyal; Yoshua Bengio; Stefan Bauer (CoRR, 2021)

Discovering Latent Causal Variables via Mechanism Sparsity: A New Principle for Nonlinear ICA. - Sébastien Lachapelle; Pau Rodríguez López; Rémi Le Priol; Alexandre Lacoste; Simon Lacoste-Julien (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)

Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA. - Sébastien Lachapelle; Pau Rodríguez; Yash Sharma 001; Katie Everett; Rémi Le Priol; Alexandre Lacoste; Simon Lacoste-Julien (CLeaR, 2022)

Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. - Sai Rajeswar; Pietro Mazzaglia; Tim Verbelen; Alexandre Piché; Bart Dhoedt; Aaron C. Courville; Alexandre Lacoste (CoRR, 2022)

A General Purpose Neural Architecture for Geospatial Systems. - Nasim Rahaman; Martin Weiss; Frederik Träuble; Francesco Locatello; Alexandre Lacoste; Yoshua Bengio; Chris Pal; Li Erran Li; Bernhard Schölkopf (CoRR, 2022)

From IID to the Independent Mechanisms assumption in continual learning. - Oleksiy Ostapenko; Pau Rodríguez; Alexandre Lacoste; Laurent Charlin (AAAI Bridge Program, 2023)

Choreographer: Learning and Adapting Skills in Imagination. - Pietro Mazzaglia; Tim Verbelen; Bart Dhoedt; Alexandre Lacoste; Sai Rajeswar (ICLR, 2023)

Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. - Sai Rajeswar; Pietro Mazzaglia; Tim Verbelen; Alexandre Piché; Bart Dhoedt; Aaron C. Courville; Alexandre Lacoste (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)

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)

Tackling Climate Change with Machine Learning. - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Sasha Luccioni; Tegan Maharaj; et al. (ACM Comput. Surv., 2023)

Explaining Visual Counterfactual Explainers. - Diego A. Velázquez; Pau Rodríguez; Alexandre Lacoste; Issam H. Laradji; F. Xavier Roca; Jordi Gonzàlez 001 (Trans. Mach. Learn. Res., 2023)

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)

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies. - Sébastien Lachapelle; Pau Rodríguez López; Yash Sharma 001; Katie Everett; Rémi Le Priol; Alexandre Lacoste; Simon Lacoste-Julien (CoRR, 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)

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)

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)

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks. - Muhammad Sohail Danish; Muhammad Akhtar Munir; Syed Roshaan Ali Shah; Kartik Kuckreja; Fahad Shahbaz Khan; Paolo Fraccaro; Alexandre Lacoste; Salman H. Khan 001 (CoRR, 2024)

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)

EarthView: A Large Scale Remote Sensing Dataset for Self-Supervision. - Diego A. Velázquez; Pau Rodríguez López; Sergio Alonso; Josep M. Gonfaus; Jordi Gonzàlez 001; Gerardo Richarte; Javier Marin; Yoshua Bengio; Alexandre Lacoste (WACV (Workshops), 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)

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)

LineRetriever: Planning-Aware Observation Reduction for Web Agents. - Imene Kerboua; Sahar Omidi Shayegan; Megh Thakkar; Xing Han Lù; Massimo Caccia; Véronique Eglin; Alexandre Aussem; Jérémy Espinas; Alexandre Lacoste (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)