Matthieu Devin

Artificial Intelligence · 2011–2016

A researcher in the Science corpus: 5 papers; trusts 30 researchers and is trusted by 982 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it; #32,859 of 35,345 by trust here, #691 by citations
• Computer Vision and Pattern Recognition — 64 citations into it; #1,401 of 21,575 by trust here, #391 by citations
• Optimization & Training — 37 citations into it; #928 of 2,601 by trust here, #33 by citations
• Representation & Self-Supervised Learning — 22 citations into it; #1,619 of 3,145 by trust here, #321 by citations

Whom Matthieu Devin trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yann LeCun
3. Alex Krizhevsky
4. Yoshua Bengio
5. Quoc V. Le
6. Marc'Aurelio Ranzato
7. Honglak Lee
8. Andrew Y. Ng
9. L. Eon Bottou
10. Jia Deng

Who trusts Matthieu Devin overall

1. Yoshua Bengio
2. Li Deng
3. Quoc V. Le
4. Tara N. Sainath
5. Richard Socher
6. Bo Li
7. Wanli Ouyang
8. Andrea Vedaldi
9. Abhinav Kumar Gupta
10. Sergey Levine

Papers from Matthieu Devin's perspective

Ordered by how strongly the researchers Matthieu Devin trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• TensorFlow: A system for large-scale machine learning (2016) — 19,838 citations
• Building high-level features using large scale unsupervised learning (2011) — 2,318 citations
• Multilingual acoustic models using distributed deep neural networks (2013) — 330 citations
• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (2016) — 11,798 citations
• Large Scale Distributed Deep Networks (2012) — 4,179 citations