Yoshua Bengio

Deep learning
Yann LeCun, Yoshua Bengio, Geoffrey E. Hinton
2015Nature84K citations Open access
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Gradient-based learning applied to document recognition
Yoshua Bengio, Léon Bottou, Yoshua Bengio, Patrick Haffner
1998Proceedings of the IEEE59K citations Open access
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Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merriënboer, Çağlar Gülçehre, Dzmitry Bahdanau +3 more
2014Conference on Empirical Methods in Natural Language Processing (EMNLP)25K citations Open access
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu +4 more
2020Communications of the ACM18K citations
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Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio
2014arXiv (Cornell University)16K citations Open access
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot, Yoshua Bengio
201014K citations
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Representation Learning: A Review and New Perspectives
Yoshua Bengio, Aaron C. Courville, Pascal Vincent
2013IEEE Transactions on Pattern Analysis and Machine Intelligence13K citations
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Graph Attention Networks
Petar Veličković, Casanova, A, P Liò, Guillem Cucurull +2 more
2017arXiv (Cornell University)12K citations Open access
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Deep Learning
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville
201612K citations
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Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Chung, Junyoung, Çağlar Gülçehre, Kyunghyun Cho, Yoshua Bengio
2014arXiv (Cornell University)11K citations Open access
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Learning long-term dependencies with gradient descent is difficult
Yoshua Bengio, P. Simard, Paolo Frasconi
1994IEEE Transactions on Neural Networks8,533 citations
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Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Kelvin Xu, Jimmy Lei Ba, Ryan Kiros, Kyunghyun Cho +4 more
2015arXiv (Cornell University)8,248 citations Open access
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Random search for hyper-parameter optimization
James Bergstra, Yoshua Bengio, Léon Bottou
20128,010 citations
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Extracting and composing robust features with denoising autoencoders
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol
2008International Conference on Machine Learning7,425 citations
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On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
Kyunghyun Cho, Bart van Merriënboer, Dzmitry Bahdanau, Yoshua Bengio
20147,245 citations Open access
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Learning Deep Architectures for AI
Yoshua Bengio
2009Foundations and Trends® in Machine Learning7,022 citations
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Deep Sparse Rectifier Neural Networks
Xavier Glorot, Antoine Bordes, Yoshua Bengio
20116,992 citations
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Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio +1 more
20106,090 citations
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How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio, Hod Lipson
2014arXiv (Cornell University)6,062 citations Open access
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston
2009International Conference on Machine Learning5,345 citations
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Learning Deep Architectures for AI
Yoshua Bengio
2009now publishers, Inc. eBooks4,941 citations
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Greedy Layer-Wise Training of Deep Networks
Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle
2007The MIT Press eBooks4,839 citations
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Convolutional networks for images, speech, and time series
Yann LeCun, Yoshua Bengio
1998HAL (Le Centre pour la Communication Scientifique Directe)4,627 citations
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Generative Adversarial Networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu +4 more
2014arXiv (Cornell University)4,474 citations Open access
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Proceedings of the 21st International Conference on Neural Information Processing Systems
Daphne Koller, Dale Schuurmans, Yoshua Bengio, Léon Bottou
20084,460 citations
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On the difficulty of training Recurrent Neural Networks
Razvan Pascanu, Tomáš Mikolov, Yoshua Bengio
2012arXiv (Cornell University)4,163 citations Open access
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Algorithms for Hyper-Parameter Optimization
James Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl
20113,939 citations Open access
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A Neural Probabilistic Language Model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Jauvin +4 more
20003,451 citations
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Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merriënboer, Çağlar Gülçehre, Dzmitry Bahdanau +3 more
2014arXiv (Cornell University)3,310 citations Open access
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Brain tumor segmentation with Deep Neural Networks
Mohammad Havaei, Axel Davy, David Warde-Farley, Antoine Biard +5 more
2016Medical Image Analysis3,272 citations Open access
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FitNets: Hints for Thin Deep Nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang +2 more
2014arXiv (Cornell University)2,859 citations Open access
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Practical Recommendations for Gradient-Based Training of Deep Architectures
Yoshua Bengio
2012Lecture notes in computer science2,238 citations Open access
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Why Does Unsupervised Pre-training Help Deep Learning?
Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol +2 more
20102,166 citations
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BinaryConnect: Training Deep Neural Networks with binary weights during propagations
Matthieu Courbariaux, Yoshua Bengio, Jean‐Pierre David
2015arXiv (Cornell University)2,109 citations Open access
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Attention-Based Models for Speech Recognition
Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho +1 more
2015arXiv (Cornell University)2,021 citations Open access
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Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
Matthieu Courbariaux, Itay Hubara, Daniel Soudry, Ran El‐Yaniv +1 more
2016arXiv (Cornell University)2,014 citations Open access
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Learning deep representations by mutual information estimation and maximization
R Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal +3 more
2018arXiv (Cornell University)1,914 citations Open access
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Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Yoshua Bengio, Nicholas Léonard, Aaron C. Courville
2013arXiv (Cornell University)1,909 citations Open access
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Word Representations: A Simple and General Method for Semi-Supervised Learning
Joseph P. Turian, Lev Ratinov, Yoshua Bengio
20101,906 citations
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Scientific discovery in the age of artificial intelligence
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao +26 more
2023Nature1,803 citations Open access
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio +3 more
2018Conference on Empirical Methods in Natural Language Processing (EMNLP)1,798 citations Open access
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The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
Simon Jégou, Michal Drozdzal, David Vázquez, Adriana Romero +1 more
2017IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)1,751 citations Open access
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A Structured Self-attentive Sentence Embedding
Zhouhan Lin, Minwei Feng, Cícero Nogueira dos Santos, Mo Yu +3 more
2017arXiv (Cornell University)1,743 citations Open access
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Challenges in Representation Learning: A Report on Three Machine Learning Contests
Ian Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville +24 more
2013Lecture notes in computer science1,715 citations
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Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville +1 more
2016AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))1,637 citations Open access
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Static Analysis of Shape in TensorFlow Programs
The Theano Development Team, Rami Al‐Rfou, Guillaume Alain, Amjad Almahairi +96 more
2016arXiv (Cornell University)1,589 citations Open access
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Semi-supervised Learning by Entropy Minimization
Yves Grandvalet, Yoshua Bengio
20041,567 citations
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Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach
Xavier Glorot, Antoine Bordes, Yoshua Bengio
20111,553 citations
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Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El‐Yaniv +1 more
2016arXiv (Cornell University)1,551 citations Open access
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NICE: Non-linear Independent Components Estimation
Laurent Dinh, David Krueger, Yoshua Bengio
2014arXiv (Cornell University)1,492 citations Open access
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Most-cited papers