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- Publications
- Influence

Gradient-based learning applied to document recognition

- Y. LeCun, L. Bottou, Yoshua Bengio, P. Haffner
- Computer Science
- 1998

Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture,… Expand

Generative Adversarial Nets

- Ian J. Goodfellow, Jean Pouget-Abadie, +5 authors Yoshua Bengio
- Computer Science
- NIPS
- 8 December 2014

We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a… Expand

Neural Machine Translation by Jointly Learning to Align and Translate

- Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio
- Computer Science, Mathematics
- ICLR
- 1 September 2014

Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single… Expand

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

- Kyunghyun Cho, B. V. Merrienboer, +4 authors Yoshua Bengio
- Computer Science, Mathematics
- EMNLP
- 3 June 2014

In this paper, we propose a novel neural network model called RNN Encoder‐ Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixedlength… Expand

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

- J. Chung, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio
- Computer Science
- ArXiv
- 10 December 2014

In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long… Expand

Deep Learning

- I. Goodfellow, Yoshua Bengio, Aaron C. Courville
- Computer Science, Medicine
- Nature
- 28 May 2015

Machine-learning technology powers many aspects of modern society: from web searches to content filtering on social networks to recommendations on e-commerce websites, and it is increasingly present… Expand

On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

- Kyunghyun Cho, B. V. Merrienboer, Dzmitry Bahdanau, Yoshua Bengio
- Computer Science, Mathematics
- SSST@EMNLP
- 3 September 2014

Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of an encoder and a… Expand

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

- Kelvin Xu, Jimmy Ba, +5 authors Yoshua Bengio
- Computer Science, Mathematics
- ICML
- 10 February 2015

Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe the content of images. We describe how we can train… Expand

Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

- P. Vincent, H. Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol
- Computer Science, Mathematics
- J. Mach. Learn. Res.
- 1 March 2010

We explore an original strategy for building deep networks, based on stacking layers of denoising autoencoders which are trained locally to denoise corrupted versions of their inputs. The resulting… Expand

Learning Deep Architectures for AI

- Yoshua Bengio
- Computer Science
- Found. Trends Mach. Learn.
- 2007

Theoretical results strongly suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one… Expand