Yoshua Bengio
Microsoft (United States)(US)
Publications by Year
Research Areas
Neural Networks and Applications, Topic Modeling, Domain Adaptation and Few-Shot Learning, Generative Adversarial Networks and Image Synthesis, Natural Language Processing Techniques
Most-Cited Works
- → Deep learning(2015)79,092 cited
- → Gradient-based learning applied to document recognition(1998)56,993 cited
- → Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation(2014)23,927 cited
- → Generative adversarial networks(2020)12,997 cited
- → Representation Learning: A Review and New Perspectives(2013)12,721 cited
- Understanding the difficulty of training deep feedforward neural networks(2010)
- → Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling(2014)10,749 cited
- → Learning long-term dependencies with gradient descent is difficult