ML Anthology

Lacoste, Alexandre

40 publications

ICML 2025 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
ICCV 2025 GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks Muhammad Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah, Kartik Kuckreja, Fahad Shahbaz Khan, Paolo Fraccaro, Alexandre Lacoste, Salman Khan
NeurIPS 2025 How to Train Your LLM Web Agent: A Statistical Diagnosis Dheeraj Vattikonda, Santhoshi Ravichandran, Emiliano Penaloza, Hadi Nekoei, Thibault Le Sellier de Chezelles, Megh Thakkar, Nicolas Gontier, Miguel Muñoz-Mármol, Sahar Omidi Shayegan, Stefania Raimondo, Xue Liu, Alexandre Drouin, Alexandre Piché, Alexandre Lacoste, Massimo Caccia
ICLR 2025 InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Amirhossein Abaskohi, Mohammad Chegini, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vazquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam H. Laradji
TMLR 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, Ori Yoran, Dehan Kong, Frank F. Xu, Siva Reddy, Graham Neubig, Quentin Cappart, Russ Salakhutdinov, Nicolas Chapados
NeurIPSW 2024 AgentMerge: Enhancing Generalization in Fine-Tuned LLM Agents Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Maxime Gasse, Alexandre Lacoste, Massimo Caccia
NeurIPSW 2024 Context Is Key: A Benchmark for Forecasting with Essential Textual Information Arjun Ashok, Andrew Robert Williams, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin
NeurIPSW 2024 Fine-Tuning Web Agents: It Works, but It's Trickier than You Think Massimo Caccia, Megh Thakkar, Léo Boisvert, Thibault Le Sellier de Chezelles, Alexandre Piché, Nicolas Chapados, Alexandre Drouin, Maxime Gasse, Alexandre Lacoste
NeurIPS 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
ICML 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 Vazquez, Nicolas Chapados, Alexandre Lacoste
ICLRW 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 Vazquez, Nicolas Chapados, Alexandre Lacoste
NeurIPSW 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 Vazquez, Christopher Pal, Alexandre Drouin
ICLR 2023 Choreographer: Learning and Adapting Skills in Imagination Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
TMLR 2023 Explaining Visual Counterfactual Explainers Diego Velazquez, Pau Rodriguez, Alexandre Lacoste, Issam H. Laradji, Xavier Roca, Jordi Gonzàlez
NeurIPS 2023 GEO-Bench: Toward Foundation Models for Earth Monitoring Alexandre Lacoste, Nils Lehmann, Pau Rodriguez, Evan Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vazquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu
ICML 2023 Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron Courville, Alexandre Lacoste
NeurIPSW 2023 The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study Rim Assouel, Tom Marty, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Sai Rajeswar, Hector Palacios, Quentin Cappart, David Vazquez, Nicolas Chapados, Maxime Gasse, Alexandre Lacoste
NeurIPSW 2022 Attention for Compositional Modularity Oleksiy Ostapenko, Pau Rodriguez, Alexandre Lacoste, Laurent Charlin
NeurIPSW 2022 Choreographer: Learning and Adapting Skills in Imagination Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
NeurIPSW 2022 Choreographer: Learning and Adapting Skills in Imagination Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
CLeaR 2022 Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sebastien Lachapelle, Pau Rodriguez, Yash Sharma, Katie E Everett, Rémi Le Priol, Alexandre Lacoste, Simon Lacoste-Julien
CLeaR 2022 Typing Assumptions Improve Identification in Causal Discovery Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sebastien Lachapelle, Alexandre Drouin
ICMLW 2022 Unsupervised Model-Based Pre-Training for Data-Efficient Reinforcement Learning from Pixels Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron Courville, Alexandre Lacoste
ICCV 2021 Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez, Massimo Caccia, Alexandre Lacoste, Lee Zamparo, Issam Laradji, Laurent Charlin, David Vazquez
ICCV 2021 Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data Oscar Mañas, Alexandre Lacoste, Xavier Giró-i-Nieto, David Vazquez, Pau Rodríguez
NeurIPS 2020 Differentiable Causal Discovery from Interventional Data Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
ECCV 2020 Embedding Propagation: Smoother Manifold for Few-Shot Classification Pau Rodríguez, Issam Laradji, Alexandre Drouin, Alexandre Lacoste
NeurIPS 2020 Online Fast Adaptation and Knowledge Accumulation (OSAKA): A New Approach to Continual Learning Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin
AISTATS 2020 Stochastic Neural Network with Kronecker Flow Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville
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, Matthew Craddock, Laurent Charlin, David Vázquez
ICML 2019 Hierarchical Importance Weighted Autoencoders Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron Courville
UAI 2019 Probability Distillation: A Caveat and Alternatives Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville
NeurIPS 2018 Improving Explorability in Variational Inference with Annealed Variational Objectives Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville
ICML 2018 Neural Autoregressive Flows Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville
NeurIPS 2018 TADAM: Task Dependent Adaptive Metric for Improved Few-Shot Learning Boris Oreshkin, Pau Rodríguez López, Alexandre Lacoste
NeurIPS 2016 PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain, Francis Bach, Alexandre Lacoste, Simon Lacoste-Julien
ICML 2014 Agnostic Bayesian Learning of Ensembles Alexandre Lacoste, Mario Marchand, François Laviolette, Hugo Larochelle
UAI 2014 Sequential Model-Based Ensemble Optimization Alexandre Lacoste, Hugo Larochelle, Mario Marchand, François Laviolette
AISTATS 2012 Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets Alexandre Lacoste, Francois Laviolette, Mario Marchand
ICML 2011 A PAC-Bayes Sample-Compression Approach to Kernel Methods Pascal Germain, Alexandre Lacoste, François Laviolette, Mario Marchand, Sara Shanian