Feifei Zhai
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 4 papers; trusts 68 researchers and is trusted by 68 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 63 citations into it; #3,586 of 35,345 by trust here, #7,010 by citations
- Natural Language Processing — 62 citations into it; #900 of 5,688 by trust here, #1,626 by citations
- Computer Vision and Pattern Recognition — 40 citations into it; #17,900 of 21,575 by trust here, #11,498 by citations
- Model Architectures — 12 citations into it
- Optimization & Training — 5 citations into it
Whom Feifei Zhai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Diederik P. Kingma
- Yoshua Bengio
- Matthew D. Zeiler
- Geoffrey E. Hinton
- Kyunghyun Cho
- Alex Krizhevsky
- Kaiming He
- Oriol Vinyals
- Jimmy Ba
Who trusts Feifei Zhai overall
- Yang Liu
- Mirella Lapata
- Pengfei Liu
- Xingxing Zhang
- Shay B. Cohen
- Ming Zhong
- Asli Celikyilmaz
- Alexios Gidiotis
- Sebastian Gehrmann
- Yen-Chun Chen
Papers from Feifei Zhai's perspective
Ordered by how strongly the researchers Feifei Zhai trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents (2016) — 1,337 citations
- Improving the Transformer Translation Model with Document-Level Context (2018) — 272 citations
- Three Strategies to Improve One-to-Many Multilingual Translation (2018) — 78 citations
- Neural Machine Translation With Explicit Phrase Alignment (2019) — 34 citations