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2020 – today
- 2024
[c13]Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin:
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. ICLR 2024- [c12]Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vázquez, Nicolas Chapados, Alexandre Lacoste:
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? ICML 2024 - [i30]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 abs/2403.07718 (2024) - [i29]Tejas Kasetty, Divyat Mahajan, Gintare Karolina Dziugaite, Alexandre Drouin, Dhanya Sridhar:
Evaluating Interventional Reasoning Capabilities of Large Language Models. CoRR abs/2404.05545 (2024) - [i28]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 abs/2407.05291 (2024) - [i27]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 abs/2407.06423 (2024) - [i26]Philippe Brouillard, Sébastien Lachapelle, Julia Kaltenborn, Yaniv Gurwicz, Dhanya Sridhar, Alexandre Drouin, Peer Nowack, Jakob Runge, David Rolnick:
Causal Representation Learning in Temporal Data via Single-Parent Decoding. CoRR abs/2410.07013 (2024) - [i25]Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours, Alexandre Drouin, Pascal Germain:
Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning. CoRR abs/2410.13577 (2024) - [i24]Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados, Alexandre Drouin:
Context is Key: A Benchmark for Forecasting with Essential Textual Information. CoRR abs/2410.18959 (2024) - 2023
- [c11]Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados:
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. ICML 2023: 23958-24004 - [c10]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 - [i23]Étienne Marcotte, Valentina Zantedeschi, Alexandre Drouin, Nicolas Chapados:
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts. CoRR abs/2304.09836 (2023) - [i22]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 abs/2306.03831 (2023) - [i21]Thibaud Godon, Baptiste Bauvin, Pascal Germain, Jacques Corbeil, Alexandre Drouin:
Invariant Causal Set Covering Machines. CoRR abs/2306.04777 (2023) - [i20]Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster, Alexandre Drouin:
Causal Discovery with Language Models as Imperfect Experts. CoRR abs/2307.02390 (2023) - [i19]Chris Chinenye Emezue, Alexandre Drouin, Tristan Deleu, Stefan Bauer, Yoshua Bengio:
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation. CoRR abs/2307.04988 (2023) - [i18]Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Nicolas Chapados, Alexandre Drouin:
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. CoRR abs/2310.01327 (2023) - [i17]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 abs/2310.08278 (2023) - [i16]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 abs/2312.13876 (2023) - 2022
- [c9]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CLeaR 2022: 162-177 - [c8]Alexandre Drouin, Étienne Marcotte, Nicolas Chapados:
TACTiS: Transformer-Attentional Copulas for Time Series. ICML 2022: 5447-5493 - [i15]Alexandre Drouin, Étienne Marcotte, Nicolas Chapados:
TACTiS: Transformer-Attentional Copulas for Time Series. CoRR abs/2202.03528 (2022) - [i14]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 abs/2208.06436 (2022) - 2021
- [i13]Xiang Zhang, Alexandre Drouin, Raymond Li:
byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings. CoRR abs/2106.13302 (2021) - [i12]Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sébastien Lachapelle, Alexandre Drouin:
Typing assumptions improve identification in causal discovery. CoRR abs/2107.10703 (2021) - [i11]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 abs/2112.00570 (2021) - 2020
- [c7]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: 62-66 - [c6]Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste:
Embedding Propagation: Smoother Manifold for Few-Shot Classification. ECCV (26) 2020: 121-138 - [c5]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. NeurIPS 2020 - [c4]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 - [c3]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 - [i10]Pau Rodríguez, Issam H. Laradji, Alexandre Drouin, Alexandre Lacoste:
Embedding Propagation: Smoother Manifold for Few-Shot Classification. CoRR abs/2003.04151 (2020) - [i9]Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin:
Differentiable Causal Discovery from Interventional Data. CoRR abs/2007.01754 (2020) - [i8]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 abs/2009.06415 (2020) - [i7]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 abs/2010.11924 (2020)
2010 – 2019
- 2018
- [i6]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 abs/1801.07756 (2018) - 2017
- [c2]Alexandre Drouin, Toby Hocking, François Laviolette:
Maximum Margin Interval Trees. NIPS 2017: 4947-4956 - [i5]Alexandre Drouin, Toby Dylan Hocking, François Laviolette:
Maximum Margin Interval Trees. CoRR abs/1710.04234 (2017) - 2016
- [i4]Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre, Mario Marchand, Jacques Corbeil, François Laviolette:
Large scale modeling of antimicrobial resistance with interpretable classifiers. CoRR abs/1612.01030 (2016) - 2015
- [i3]Alexandre Drouin, Sébastien Giguère, Maxime Déraspe, François Laviolette, Mario Marchand, Jacques Corbeil:
Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance. CoRR abs/1505.06249 (2015) - 2014
- [i2]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 abs/1412.1074 (2014) - 2013
- [j1]Sébastien Giguère, Mario Marchand, François Laviolette, Alexandre Drouin, Jacques Corbeil:
Learning a peptide-protein binding affinity predictor with kernel ridge regression. BMC Bioinform. 14: 82 (2013) - [c1]Maxime Latulippe, Alexandre Drouin, Philippe Giguère, François Laviolette:
Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning. IJCAI 2013: 2480-2487 - 2012
- [i1]Sébastien Giguère, Mario Marchand, François Laviolette, Alexandre Drouin, Jacques Corbeil:
Learning a peptide-protein binding affinity predictor with kernel ridge regression. CoRR abs/1207.7253 (2012)
Coauthor Index
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