Alexandre Drouin

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 36

Top Topics

Manifold Regularization

Causal Discovery

Synthetic Datasets

Top Venues

Publications

Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar
Evaluating Interventional Reasoning Capabilities of Large Language Models. CoRR (2024)
Léo Boisvert, Megh Thakkar, Maxime Gasse, Massimo Caccia, Thibault Le Sellier De Chezelles, Quentin Cappart, Nicolas Chapados, Alexandre Lacoste, Alexandre Drouin
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks. CoRR (2024)
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. ICLR (2024)
Gaurav Sahu, Abhay Puri, Juan A. Rodriguez, Alexandre Drouin, Perouz Taslakian, Valentina Zantedeschi, Alexandre Lacoste, David Vázquez, Nicolas Chapados, Christopher Pal, Sai Rajeswar, Issam Hadj Laradji
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation. CoRR (2024)
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
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks? CoRR (2024)
Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. CoRR (2023)
Thibaud Godon, Baptiste Bauvin, Pascal Germain, Jacques Corbeil, Alexandre Drouin
Invariant Causal Set Covering Machines. CoRR (2023)
Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu
GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR (2023)
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. CoRR (2023)
Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster, Alexandre Drouin
Causal Discovery with Language Models as Imperfect Experts. CoRR (2023)
Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. CoRR (2023)
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
Lag-Llama: Towards Foundation Models for Time Series Forecasting. CoRR (2023)
Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. ICML (2023)
Issam H. Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vázquez, Christopher Pal, Alexandre Drouin
Capture the Flag: Uncovering Data Insights with Large Language Models. CoRR (2023)
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
GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS (2023)
Alexandre Drouin, Étienne Marcotte, Nicolas Chapados
TACTiS: Transformer-Attentional Copulas for Time Series. ICML (2022)
Alexandre Drouin, Étienne Marcotte, Nicolas Chapados
TACTiS: Transformer-Attentional Copulas for Time Series. CoRR (2022)
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
Typing assumptions improve identification in causal discovery. CLeaR (2022)
Thibaud Godon, Pier-Luc Plante, Baptiste Bauvin, Elina Francovic-Fontaine, Alexandre Drouin, Jacques Corbeil
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data. CoRR (2022)
Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin
Typing assumptions improve identification in causal discovery. CoRR (2021)
Xiang Zhang, Alexandre Drouin, Raymond Li
byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings. CoRR (2021)
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
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. CoRR (2021)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. NeurIPS (2020)
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
In search of robust measures of generalization. NeurIPS (2020)
Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste
Embedding Propagation: Smoother Manifold for Few-Shot Classification. CoRR (2020)
Alexandre Lacoste, Pau Rodríguez, Frédéric Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam H. Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
Synbols: Probing Learning Algorithms with Synthetic Datasets. CoRR (2020)
Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin
Differentiable Causal Discovery from Interventional Data. CoRR (2020)
Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy
In Search of Robust Measures of Generalization. CoRR (2020)
Faizy Ahsan, Alexandre Drouin, François Laviolette, Doina Precup, Mathieu Blanchette
Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites. BIBM (2020)
Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste
Embedding Propagation: Smoother Manifold for Few-Shot Classification. ECCV (26) (2020)
Alexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez
Synbols: Probing Learning Algorithms with Synthetic Datasets. NeurIPS (2020)
Ulysse Côté Allard, Cheikh Latyr Fall, Alexandre Drouin, Alexandre Campeau-Lecours, Clément Gosselin, Kyrre Glette, François Laviolette, Benoit Gosselin
Deep Learning for Electromyographic Hand Gesture Signal Classification by Leveraging Transfer Learning. CoRR (2018)
Alexandre Drouin, Toby Dylan Hocking, François Laviolette
Maximum Margin Interval Trees. CoRR (2017)
Alexandre Drouin, Toby Hocking, François Laviolette
Maximum Margin Interval Trees. NIPS (2017)
Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre, Mario Marchand, Jacques Corbeil, François Laviolette
Large scale modeling of antimicrobial resistance with interpretable classifiers. CoRR (2016)
Alexandre Drouin, Sébastien Giguère, Maxime Déraspe, François Laviolette, Mario Marchand, Jacques Corbeil
Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance. CoRR (2015)
Alexandre Drouin, Sébastien Giguère, Vladana Sagatovich, Maxime Déraspe, François Laviolette, Mario Marchand, Jacques Corbeil
Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine. CoRR (2014)
Maxime Latulippe, Alexandre Drouin, Philippe Giguère, François Laviolette
Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning. IJCAI (2013)
Sébastien Giguère, Mario Marchand, François Laviolette, Alexandre Drouin, Jacques Corbeil
Learning a peptide-protein binding affinity predictor with kernel ridge regression. BMC Bioinform. 14 (2013)
Sébastien Giguère, Mario Marchand, François Laviolette, Alexandre Drouin, Jacques Corbeil
Learning a peptide-protein binding affinity predictor with kernel ridge regression CoRR (2012)