Search Results for author: Alexandre Drouin

Found 13 papers, 8 papers with code

TACTiS: Transformer-Attentional Copulas for Time Series

no code implementations7 Feb 2022 Alexandre Drouin, Étienne Marcotte, Nicolas Chapados

The estimation of time-varying quantities is a fundamental component of decision making in fields such as healthcare and finance.

Decision Making Time Series

Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark

no code implementations1 Dec 2021 Alexandre Lacoste, Evan David Sherwin, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, Pau Rodriguez, David Vazquez

Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to impressive increases in generalisation for downstream tasks.

Benchmark Natural Language Processing

Typing assumptions improve identification in causal discovery

1 code implementation22 Jul 2021 Philippe Brouillard, Perouz Taslakian, Alexandre Lacoste, Sebastien Lachapelle, Alexandre Drouin

Causal discovery from observational data is a challenging task that can only be solved up to a set of equivalent solutions, called an equivalence class.

Causal Discovery

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

no code implementations24 Jun 2021 Xiang Zhang, Alexandre Drouin, Raymond Li

This article introduces byteSteady -- a fast model for classification using byte-level n-gram embeddings.

Classification Text Classification

In Search of Robust Measures of Generalization

1 code implementation NeurIPS 2020 Gintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy

A large volume of work aims to close this gap, primarily by developing bounds on generalization error, optimization error, and excess risk.

Generalization Bounds

Differentiable Causal Discovery from Interventional Data

1 code implementation NeurIPS 2020 Philippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin

This work constitutes a new step in this direction by proposing a theoretically-grounded method based on neural networks that can leverage interventional data.

Causal Discovery

Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

4 code implementations10 Jan 2018 Ulysse Côté-Allard, Cheikh Latyr Fall, Alexandre Drouin, Alexandre Campeau-Lecours, Clément Gosselin, Kyrre Glette, François Laviolette, Benoit Gosselin

Consequently, this paper proposes applying transfer learning on aggregated data from multiple users, while leveraging the capacity of deep learning algorithms to learn discriminant features from large datasets.

EMG Gesture Recognition General Classification +2

Maximum Margin Interval Trees

1 code implementation NeurIPS 2017 Alexandre Drouin, Toby Dylan Hocking, François Laviolette

Learning a regression function using censored or interval-valued output data is an important problem in fields such as genomics and medicine.


Large scale modeling of antimicrobial resistance with interpretable classifiers

1 code implementation3 Dec 2016 Alexandre Drouin, Frédéric Raymond, Gaël Letarte St-Pierre, Mario Marchand, Jacques Corbeil, François Laviolette

Antimicrobial resistance is an important public health concern that has implications in the practice of medicine worldwide.

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