Jianfei Yu

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 59 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it; #9,311 of 35,345 by trust here, #23,731 by citations
• Natural Language Processing — 29 citations into it; #1,894 of 5,688 by trust here, #4,449 by citations
• Model Architectures — 8 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Management Science and Operations Research — 5 citations into it

Whom Jianfei Yu trusts overall

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

1. Geoffrey E. Hinton
2. Jimmy Ba
3. Yoshua Bengio
4. Jacob Devlin
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Kaiming He
8. Ilya Sutskever
9. Xavier Glorot
10. Yann LeCun

Who trusts Jianfei Yu overall

1. Ringki Das
2. Lei Zhang
3. Jeremy Barnes
4. Shuai Wang
5. Georgios Chochlakis
6. Hao Zhang
7. Guangyi Lv
8. Douwe Kiela
9. Thoudam Doren Singh
10. Sebastian Ruder

Papers from Jianfei Yu's perspective

Ordered by how strongly the researchers Jianfei Yu 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. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer (2020) — 331 citations
• Adapting BERT for Target-Oriented Multimodal Sentiment Classification (2019) — 319 citations
• Learning Sentence Embeddings with Auxiliary Tasks for Cross-Domain Sentiment Classification (2016) — 195 citations