Yoshua Bengio

Research interests

Publications

• Scientific discovery in the age of artificial intelligence

  Nature · 2023 · https://doi.org/10.1038/s41586-023-06221-2

• Tackling Climate Change with Machine Learning

  OPUS 4 (Zuse Institute Berlin) · 2022 · https://doi.org/10.1145/3485128

• Toward Causal Representation Learning

  Proceedings of the IEEE · 2021 · https://doi.org/10.1109/jproc.2021.3058954

• Generative adversarial networks

  Communications of the ACM · 2020 · https://doi.org/10.1145/3422622

• HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

  Journal · 2018 · https://doi.org/10.18653/v1/d18-1259

• Graph Attention Networks

  arXiv (Cornell University) · 2017

• Deep Learning

  Journal · 2016

• Deep learning

  Nature · 2015 · 10.1038/nature14539

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

  arXiv (Cornell University) · 2015 · 10.48550/arxiv.1502.03044

• On the Properties of Neural Machine Translation: Encoder–Decoder Approaches

  Journal · 2014 · 10.3115/v1/w14-4012

• Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

  arXiv (Cornell University) · 2014 · 10.48550/arxiv.1412.3555

• Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

  Journal · 2014 · 10.3115/v1/d14-1179

• Generative Adversarial Networks

  arXiv (Cornell University) · 2014 · 10.48550/arxiv.1406.2661

• Neural Machine Translation by Jointly Learning to Align and Translate

  arXiv (Cornell University) · 2014 · 10.48550/arxiv.1409.0473

• Representation Learning: A Review and New Perspectives

  IEEE Transactions on Pattern Analysis and Machine Intelligence · 2013 · 10.1109/tpami.2013.50

• Random search for hyper-parameter optimization

  Journal · 2012

• On the difficulty of training Recurrent Neural Networks

  arXiv (Cornell University) · 2012 · 10.48550/arxiv.1211.5063

• Deep Sparse Rectifier Neural Networks

  Journal · 2011

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

  Journal · 2010

• Understanding the difficulty of training deep feedforward neural networks

  Journal · 2010

• Learning Deep Architectures for AI

  Foundations and Trends® in Machine Learning · 2009 · 10.1561/2200000006

• Curriculum learning

  Journal · 2009 · 10.1145/1553374.1553380

• Learning Deep Architectures for AI

  now publishers, Inc. eBooks · 2009 · 10.1561/9781601982957

• Extracting and composing robust features with denoising autoencoders

  Journal · 2008 · 10.1145/1390156.1390294

• Proceedings of the 21st International Conference on Neural Information Processing Systems

  Journal · 2008

• Greedy Layer-Wise Training of Deep Networks

  The MIT Press eBooks · 2007 · 10.7551/mitpress/7503.003.0024

• Object Recognition with Gradient-Based Learning

  Lecture notes in computer science · 1999 · 10.1007/3-540-46805-6_19

• Gradient-based learning applied to document recognition

  Proceedings of the IEEE · 1998 · 10.1109/5.726791

• Convolutional networks for images, speech, and time series

  HAL (Le Centre pour la Communication Scientifique Directe) · 1998 · 10.5555/303568.303704

• Learning long-term dependencies with gradient descent is difficult

  IEEE Transactions on Neural Networks · 1994 · 10.1109/72.279181

Current projects

No projects listed.