Shihao Gu

Finance · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 37 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Finance — 29 citations into it; #5,011 of 10,518 by trust here, #4,858 by citations
• Economics and Econometrics — 26 citations into it
• Statistics and Probability — 16 citations into it
• Management Science and Operations Research — 14 citations into it; #5,211 of 11,946 by trust here, #4,746 by citations
• Model Architectures — 14 citations into it
• Artificial Intelligence — 12 citations into it
• Optimization & Training — 11 citations into it
• Accounting — 8 citations into it

Whom Shihao Gu trusts overall

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

1. Diederik P. Kingma
2. Yann LeCun
3. Geoffrey E. Hinton
4. Jerome H. Friedman
5. Yoshua Bengio
6. Sergey Ioffe
7. Kaiming He
8. Jimmy Ba
9. Trevor J. Hastie
10. Ken West

Who trusts Shihao Gu overall

1. Luyang Chen
2. Ji Hyung Lee
3. Daniele Bianchi
4. Marcelo C. Medeiros
5. Markus Pelger
6. Zhentao Shi
7. M. Büchner
8. Hamed Ghoddusi
9. Jason Zhu
10. Gabriel F. R. Vasconcelos

Papers from Shihao Gu's perspective

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

Their papers

• Empirical Asset Pricing via Machine Learning (2018) — 2,086 citations
• Autoencoder asset pricing models (2020) — 364 citations