Zhen-Le Yang

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 106 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it; #14,137 of 35,345 by trust here, #12,761 by citations
• Natural Language Processing — 39 citations into it; #2,622 of 5,688 by trust here, #2,732 by citations
• Computer Vision and Pattern Recognition — 28 citations into it; #9,228 of 21,575 by trust here, #8,831 by citations
• Model Architectures — 12 citations into it
• Generative Models — 10 citations into it; #1,374 of 1,956 by trust here, #1,336 by citations
• Representation & Self-Supervised Learning — 6 citations into it

Whom Zhen-Le Yang trusts overall

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

1. Yoshua Bengio
2. Kyunghyun Cho
3. Ilya Sutskever
4. Dzmitry Bahdanau
5. Geoffrey E. Hinton
6. Rico Sennrich
7. Diederik P. Kingma
8. Tomas Mikolov
9. Alex Krizhevsky
10. Yann LeCun

Who trusts Zhen-Le Yang overall

1. Mikel Artetxe
2. Viktor Hangya
3. Gorka Labaka
4. Surangika Ranathunga
5. Cristóbal Esteban
6. Leshem Choshen
7. Yang Feng
8. Shuo Ren
9. Nima Pourdamghani
10. Ishaan Gulrajani

Papers from Zhen-Le Yang's perspective

Ordered by how strongly the researchers Zhen-Le Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets (2017) — 173 citations
• Unsupervised Neural Machine Translation with Weight Sharing (2018) — 131 citations