Alexandre Drouin

According to our database, Alexandre Drouin authored at least 26 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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, Nicolas Chapados, Alexandre Lacoste

CoRR, 2024

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, Christopher Pal, Alexandre Drouin

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, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish

CoRR, 2023

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series.

Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, 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

Causal Discovery with Language Models as Imperfect Experts.

Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster, Alexandre Drouin

CoRR, 2023

Invariant Causal Set Covering Machines.

Thibaud Godon, Baptiste Bauvin, Pascal Germain, Jacques Corbeil, Alexandre Drouin

CoRR, 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, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts.

Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados

Proceedings of the International Conference on Machine Learning, 2023

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

TACTiS: Transformer-Attentional Copulas for Time Series.

Alexandre Drouin, Étienne Marcotte, Nicolas Chapados

Proceedings of the International Conference on Machine Learning, 2022

Typing assumptions improve identification in causal discovery.

Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

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

CoRR, 2021

byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings.

Xiang Zhang, Alexandre Drouin, Raymond Li

CoRR, 2021

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

In search of robust measures of generalization.

Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Causal Discovery from Interventional Data.

Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Embedding Propagation: Smoother Manifold for Few-Shot Classification.

Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste

Proceedings of the Computer Vision - ECCV 2020, 2020

Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites.

Faizy Ahsan, Alexandre Drouin, François Laviolette, Doina Precup, Mathieu Blanchette

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2018

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

2017

Maximum Margin Interval Trees.

Alexandre Drouin, Toby Hocking, François Laviolette

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

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

2015

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

2014

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

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

Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning.

Maxime Latulippe, Alexandre Drouin, Philippe Giguère, François Laviolette

Proceedings of the IJCAI 2013, 2013