Alexandre Drouin
Alexandre Drouin
Lead Research Scientist, ServiceNow Research -- Adjunct Professor of Computer Science, ULaval
Verified email at - Homepage
Cited by
Evaluating Interventional Reasoning Capabilities of Large Language Models
T Kasetty, D Mahajan, GK Dziugaite, A Drouin, D Sridhar
arXiv preprint arXiv:2404.05545, 2024
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
A Drouin, M Gasse, M Caccia, IH Laradji, M Del Verme, T Marty, ...
arXiv preprint arXiv:2403.07718, 2024
Geo-bench: Toward foundation models for earth monitoring
A Lacoste, N Lehmann, P Rodriguez, E Sherwin, H Kerner, B Lütjens, ...
Advances in Neural Information Processing Systems 36, 2024
Capture the Flag: Uncovering Data Insights with Large Language Models
I Laradji, P Taslakian, S Rajeswar, V Zantedeschi, A Lacoste, ...
arXiv preprint arXiv:2312.13876, 2023
The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study
R Assouel, T Marty, M Caccia, IH Laradji, A Drouin, S Rajeswar, ...
NeurIPS 2023 Foundation Models for Decision Making Workshop, 2023
Lag-llama: Towards foundation models for time series forecasting
K Rasul, A Ashok, AR Williams, A Khorasani, G Adamopoulos, ...
arXiv preprint arXiv:2310.08278, 2023
Tactis-2: Better, faster, simpler attentional copulas for multivariate time series
A Ashok, É Marcotte, V Zantedeschi, N Chapados, A Drouin
arXiv preprint arXiv:2310.01327, 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
CC Emezue, A Drouin, T Deleu, S Bauer, Y Bengio
arXiv preprint arXiv:2307.04988, 2023
Causal discovery with language models as imperfect experts
S Long, A Piché, V Zantedeschi, T Schuster, A Drouin
arXiv preprint arXiv:2307.02390, 2023
Regions of reliability in the evaluation of multivariate probabilistic forecasts
É Marcotte, V Zantedeschi, A Drouin, N Chapados
International Conference on Machine Learning, 23958-24004, 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
C Chinenye Emezue, A Drouin, T Deleu, S Bauer, Y Bengio
arXiv e-prints, arXiv: 2307.04988, 2023
Invariant Causal Set Covering Machines
T Godon, B Bauvin, P Germain, J Corbeil, A Drouin
arXiv preprint arXiv:2306.04777, 2023
Using Typed Data for Causal Fault Discovery in Networks
A Drouin, A Lacoste, P Taslakian, P Brouillard, S Lachapelle
US Patent App. 17/466,376, 2023
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data
T Godon, PL Plante, B Bauvin, E Francovic-Fontaine, A Drouin, J Corbeil
arXiv preprint arXiv:2208.06436, 2022
TACTiS: Transformer-attentional copulas for time series
A Drouin, É Marcotte, N Chapados
International Conference on Machine Learning, 5447-5493, 2022
Typing assumptions improve identification in causal discovery
P Brouillard, P Taslakian, A Lacoste, S Lachapelle, A Drouin
Conference on Causal Learning and Reasoning, 162-177, 2022
Toward foundation models for earth monitoring: Proposal for a climate change benchmark
A Lacoste, ED Sherwin, H Kerner, H Alemohammad, B Lütjens, J Irvin, ...
arXiv preprint arXiv:2112.00570, 2021
bytesteady: Fast classification using byte-level n-gram embeddings
X Zhang, A Drouin, R Li
arXiv preprint arXiv:2106.13302, 2021
Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites
F Ahsan, A Drouin, F Laviolette, D Precup, M Blanchette
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
P Rodríguez, I Laradji, A Drouin, A Lacoste
ECCV 2020, 2020
The system can't perform the operation now. Try again later.
Articles 1–20