Jing Liu

Artificial Intelligence · with Cai · 2021

A researcher in the Science corpus: 1 paper; trusts 195 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 52 citations into it; #27,650 of 35,345 by trust here, #34,213 by citations
• Computer Vision and Pattern Recognition — 48 citations into it; #17,112 of 21,575 by trust here, #21,103 by citations
• Efficiency & Compression — 17 citations into it
• Optimization & Training — 14 citations into it
• Model Architectures — 10 citations into it

Whom Jing Liu trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Geoffrey E. Hinton
6. Ronald J. Williams
7. Andrew Zisserman
8. Yann LeCun
9. Ilya Sutskever
10. Quoc V. Le

Who trusts Jing Liu overall

1. Alexandre D'efossez
2. Sein Park
3. Yossi Adi
4. Junhyuk So

Papers from Jing Liu's perspective

Ordered by how strongly the researchers Jing Liu 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Sharpness-aware Quantization for Deep Neural Networks (2021) — 30 citations