Jiawei Chen

Artificial Intelligence · with Feng · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 251 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 109 citations into it; #26,548 of 35,345 by trust here, #23,077 by citations
• Computer Vision and Pattern Recognition — 88 citations into it; #18,828 of 21,575 by trust here, #14,478 by citations
• Information Systems — 75 citations into it; #8,259 of 8,771 by trust here, #4,682 by citations
• Management Science and Operations Research — 44 citations into it; #11,594 of 11,946 by trust here, #5,787 by citations
• Generative Models — 23 citations into it
• Safety, Robustness & Interpretability — 18 citations into it
• Safety Research — 14 citations into it
• Marketing — 12 citations into it

Whom Jiawei Chen trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Krizhevsky
6. Harald Steck
7. Thorsten Joachims
8. Yann LeCun
9. Ilya Sutskever
10. Xiangnan He

Who trusts Jiawei Chen overall

1. Jinglin Liu
2. Junliang Yu
3. Feiyang Chen
4. Yi Ren
5. Xu Tan
6. Xiangnan He
7. Chengxi Li
8. Le Wu
9. Chongming Gao
10. Tianxin Wei

Papers from Jiawei Chen's perspective

Ordered by how strongly the researchers Jiawei 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Image Blind Denoising with Generative Adversarial Network Based Noise Modeling (2018) — 568 citations
• Bias and Debias in Recommender System: A Survey and Future Directions (2020) — 923 citations
• Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation (2020) — 34 citations
• HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis (2020) — 114 citations
• Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System (2020) — 403 citations