Bengio, Yoshua

Deep learning

LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature

Neural Networks and ApplicationsAdvanced Neural Network Applications

Cited by 84,126

Gradient-based learning applied to document recognition

Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE

Handwritten Text Recognition TechniquesVehicle License Plate Recognition

Cited by 58,805

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

Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Natural Language Processing TechniquesTopic Modeling

Cited by 25,545

Generative adversarial networks

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2020) · Communications of the ACM

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 18,384

Neural Machine Translation by Jointly Learning to Align and Translate

Bahdanau, D., Cho, K., & Bengio, Y. (2014) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 16,213

Representation Learning: A Review and New Perspectives

Bengio, Y., Courville, A., & Vincent, P. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 13,001

Graph Attention Networks

Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., & Bengio, Y. (2017) · arXiv

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 12,107

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014) · arXiv

Neural Networks and ApplicationsSpeech Recognition and Synthesis

Cited by 11,008

Learning long-term dependencies with gradient descent is difficult

Bengio, Y., Simard, P., & Frasconi, P. (1994) · IEEE Transactions on Neural Networks

Neural Networks and ApplicationsNeural Networks and Reservoir Computing

Cited by 8,542

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

Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 8,248

Extracting and composing robust features with denoising autoencoders

Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08

Neural Networks and ApplicationsFace and Expression Recognition

Cited by 7,436

How transferable are features in deep neural networks?

Yosinski, J., Clune, J., Bengio, Y., & Lipson, H. (2014) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 6,061

Curriculum learning

Bengio, Y., Louradour, J., Collobert, R., & Weston, J. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning

Stochastic Gradient Optimization TechniquesReinforcement Learning in Robotics

Cited by 5,366

Greedy layer-wise training of deep networks

Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 4,841

Generative Adversarial Networks

Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014) · arXiv

Generative Adversarial Networks and Image SynthesisTopic Modeling

Cited by 4,477

On the difficulty of training recurrent neural networks

Pascanu, R., Mikolov, T., & Bengio, Y. (2012) · arXiv

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 4,310

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

Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 3,317

Brain tumor segmentation with Deep Neural Networks

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2017) · Medical Image Analysis

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 3,278

Brain Tumor Segmentation with Deep Neural Networks

Havaei, M., Davy, A., Warde-Farley, D., Biard, A., Courville, A., Bengio, Y., Pal, C., Jodoin, P.-M., & Larochelle, H. (2015) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 3,278

FitNets: Hints for Thin Deep Nets

Romero, A., Ballas, N., Kahou, S. E., Chassang, A., Gatta, C., & Bengio, Y. (2014) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,859

Practical Recommendations for Gradient-Based Training of Deep Architectures

Bengio, Y. (2012) · Lecture Notes in Computer Science

Neural Networks and ApplicationsStochastic Gradient Optimization Techniques

Cited by 2,259

BinaryConnect: Training Deep Neural Networks with binary weights during propagations

Courbariaux, M., Bengio, Y., & David, J.-P. (2015) · arXiv

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 2,180

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

Courbariaux, M., Hubara, I., Soudry, D., El-Yaniv, R., & Bengio, Y. (2016) · arXiv

Advanced Neural Network ApplicationsAdvanced Memory and Neural Computing

Cited by 2,106

Attention-Based Models for Speech Recognition

Chorowski, J., Bahdanau, D., Serdyuk, D., Cho, K., & Bengio, Y. (2015) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 2,021