Nicolas Chapados

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N-BEATS: Neural basis expansion analysis for interpretable time series forecasting pdf

Nicolas Chapados, Yoshua Bengio, Boris N. Oreshkin, 2019, ICLR.

Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model

Nicolas Chapados, M. Byrne, F. Soudan, 2017, Gut.

Statistical Machine Learning Algorithms for Target Classification from Acoustic Signature

Nicolas Chapados, Yoshua Bengio, Vincent Mirelli, 2009 .

Higher-Order Feature Synthesis for Insurance Scoring Models

Nicolas Chapados, Xavier Saint-Mleux, Charles Dugas, 2009 .

Metric-based model selection for time-series forecasting

Nicolas Chapados, Yoshua Bengio, Yoshua Bengio, 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

Meta-learning framework with applications to zero-shot time-series forecasting pdf

Nicolas Chapados, Yoshua Bengio, Boris N. Oreshkin, 2020, AAAI.

Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference

Pascal Vincent, Nicolas Chapados, Yoshua Bengio, 2001, NIPS.

Forecasting and Trading Commodity Contract Spreads with Gaussian Processes

Yoshua Bengio, Nicolas Chapados, 2007 .

Method and apparatus for discourse management

Nicolas Chapados, P. Stubley, Claudia Pateras, 2002 .

Volatility Forecasting and Explanatory Variables: A Tractable Bayesian Approach to Stochastic Volatility

Nicolas Chapados, Christian Dorion, 2013 .

VolatilityForecasting andExplanatoryVariables: AT ractableBayesianApproach toStochasticVolatility

Nicolas Chapados, Christian Dorion, 2012 .

Information Fusion in Deep Convolutional Neural Networks for Biomedical Image Segmentation 1

Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, 2018, Signal Processing and Machine Learning for Biomedical Big Data.

TACTiS: Transformer-Attentional Copulas for Time Series

Alexandre Drouin, Nicolas Chapados, 'E. Marcotte, 2022, ICML.

Portfolio Choice Problems - An Introductory Survey of Single and Multiperiod Models

Nicolas Chapados, Nicolas Chapados, 2011, Springer Briefs in Electrical and Computer Engineering.

Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking

Pascal Vincent, Nicolas Chapados, Yoshua Bengio, 2003 .

Effective Bayesian Modeling of Groups of Related Count Time Series

Nicolas Chapados, Nicolas Chapados, 2014, ICML.

Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification

Stan Matwin, Mohammad Havaei, Nicolas Chapados, 2018 .

HeMIS: Hetero-Modal Image Segmentation

Mohammad Havaei, Nicolas Guizard, Nicolas Chapados, 2016, MICCAI.

Cost functions and model combination for VaR-based asset allocation using neural networks

Nicolas Chapados, Yoshua Bengio, Yoshua Bengio, 2001, IEEE Trans. Neural Networks.

Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts

Nicolas Chapados, Valentina Zantedeschi, 'E. Marcotte, 2023, 2304.09836.

Learning to Learn with Conditional Class Dependencies

Stan Matwin, Mohammad Havaei, Nicolas Chapados, 2018, ICLR.

Retail store scheduling for profit

Nicolas Chapados, Pierre L'Ecuyer, Louis-Martin Rousseau, 2014, Eur. J. Oper. Res..

Extensions to Metric-Based Model Selection

Nicolas Chapados, Yoshua Bengio, Yoshua Bengio, 2003, J. Mach. Learn. Res..

Can AI Read the Minds of Corporate Executives?

Nicolas Chapados, Ruslan Goyenko, Zhenzhen Fan, 2023, SSRN Electronic Journal.

Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization

Nicolas Chapados, Yoshua Bengio, Yoshua Bengio, 2007, J. Comput..

The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization

Nicolas Chapados, Yoshua Bengio, Yoshua Bengio, 2006, Canadian Conference on AI.

On the Importance of Attention in Meta-Learning for Few-Shot Text Classification pdf

Stan Matwin, Mohammad Havaei, Nicolas Chapados, 2018, ArXiv.

Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife

Nicolas Chapados, Louis-Martin Rousseau, Quentin Cappart, 2021, Physics in medicine and biology.

Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife

Nicolas Chapados, Louis-Martin Rousseau, Quentin Cappart, 2021 .

Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts

Alexandre Drouin, Nicolas Chapados, Valentina Zantedeschi, 2023, International Conference on Machine Learning.

DETONATION CLASSIFICATION FROM ACOUSTIC SIGNATURE WITH THE RESTRICTED BOLTZMANN MACHINE

Yoshua Bengio, H. Larochelle, Olivier Delalleau, 2012, Comput. Intell..

Detonation Classification from Acoustic Signature with the Restricted Boltzmann Machine

Nicolas Chapados, Yoshua Bengio, Hugo Larochelle, 2022 .

Dynamic Routing and Wavelength Assignment with Reinforcement Learning

Nicolas Chapados, Louis-Martin Rousseau, Quentin Cappart, 2023, INFORMS Journal on Optimization.

A high-order feature synthesis and selection algorithm applied to insurance risk modelling

Nicolas Chapados, Xavier Saint-Mleux, Charles Dugas, 2011, Int. J. Bus. Intell. Data Min..

Scoring Models for Insurance Risk Sharing Pool Opimization

Pascal Vincent, Nicolas Chapados, Charles Dugas, 2008, 2008 IEEE International Conference on Data Mining Workshops.

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Kashif Rasul, I. Rish, Nicolas Chapados, 2023, 2310.08278.

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?

Manuel Del Verme, Nicolas Chapados, Massimo Caccia, 2024, ArXiv.

StarCoder 2 and The Stack v2: The Next Generation

Leandro von Werra, Carlos Muñoz Ferrandis, Terry Yue Zhuo, 2024, ArXiv.

Extending Metric-Based Model Selection and Regularization in the Absence of Unlabeled Data

Yoshua Bengio, Nicolas Chapados, 2022 .

Série Scientifique Scientific Series Metric-based Model Selection for Time-series Forecasting

Yoshua Bengio, Nicolas Chapados, 2022 .

Capture the Flag: Uncovering Data Insights with Large Language Models

Sai Rajeswar, Nicolas Chapados, Perouz Taslakian, 2023, ArXiv.