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Yoshua Bengio

Researcher at Université de Montréal

Publications -  1146
Citations -  534376

Yoshua Bengio is an academic researcher from Université de Montréal. The author has contributed to research in topics: Artificial neural network & Deep learning. The author has an hindex of 202, co-authored 1033 publications receiving 420313 citations. Previous affiliations of Yoshua Bengio include McGill University & Centre de Recherches Mathématiques.

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Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study

TL;DR: In this article, the authors take an empirical approach to understand how these models use the available dialog history by studying the sensitivity of the models to artificially introduced unnatural changes or perturbations to their context at test time.
Book ChapterDOI

Generalization of a Parametric Learning Rule

TL;DR: A method to find new learning rules for neural networks by considering them as parametric functions and using any standard optimization method to select the parameters is proposed.
Proceedings ArticleDOI

GFlowNets and variational inference

TL;DR: This paper builds bridges between two families of probabilistic algorithms: (hi-erarchical) variational inference (VI), which is typically used to model distributions over continuous spaces, and generative networks (GFlowNets), which have been used for distributions over discrete structures such as graphs.
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On the Morality of Artificial Intelligence.

TL;DR: This article proposes both conceptual and practical principles and guidelines for ML research and deployment, insisting on concrete actions that can be taken by practitioners to pursue a more ethical and moral practice of ML aimed at using AI for social good.
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A Deep Reinforcement Learning Chatbot (Short Version)

TL;DR: MILA's MILABOT chatbot is capable of conversing with humans on popular small talk topics through both speech and text and consists of an ensemble of natural language generation and retrieval models, including neural network and template-based models.