Jingyuan Chen

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 371 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 83 citations into it; #11,511 of 21,575 by trust here, #6,426 by citations
• Artificial Intelligence — 65 citations into it
• Natural Language Processing — 19 citations into it
• Multimodal Learning — 17 citations into it
• Information Systems — 16 citations into it; #3,628 of 8,771 by trust here, #1,707 by citations
• Model Architectures — 11 citations into it
• Recommender Systems — 8 citations into it
• Optimization & Training — 7 citations into it

Whom Jingyuan Chen trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Karen Simonyan
7. Ross B. Girshick
8. Jimmy Ba
9. Ilya Sutskever
10. Yann LeCun

Who trusts Jingyuan Chen overall

1. Xiangnan He
2. Xiang Wang
3. Xu Chen
4. Le Wu
5. Xiting Wang
6. Tat-seng Chua
7. Yi Tay
8. Jonghwan Mun
9. Gabriel Ilharco
10. Guangneng Hu

Papers from Jingyuan Chen's perspective

Ordered by how strongly the researchers Jingyuan Chen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Temporally Grounding Natural Sentence in Video (2018) — 342 citations
• Learning to Segment the Tail (2020) — 93 citations
• Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention (2017) — 947 citations