Jiaoyang Huang

Statistics and Probability · 2016–2019

A researcher in the Science corpus: 4 papers; trusts 47 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 63 citations into it
• Mathematical Physics — 52 citations into it
• Artificial Intelligence — 42 citations into it; #18,979 of 35,345 by trust here, #25,040 by citations
• Discrete Mathematics and Combinatorics — 33 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Optimization & Training — 13 citations into it
• Scaling & Learning Theory — 13 citations into it; #264 of 428 by trust here, #356 by citations
• Geometry and Topology — 11 citations into it

Whom Jiaoyang Huang trusts overall

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

1. L. Erdős
2. Horng-Tzer Yau
3. Antti Knowles
4. Greg Yang
5. Terence Tao
6. S. P'ech'e
7. Jun Yin
8. Song Mei
9. Geoffrey E. Hinton
10. Yoshua Bengio

Who trusts Jiaoyang Huang overall

1. Timothy Nguyen
2. Greg Yang
3. Lechao Xiao
4. J. Alt
5. Soufiane Hayou
6. Roman Novak
7. Ethan Dyer
8. Zeyuan Allen-Zhu
9. Arka Adhikari

Papers from Jiaoyang Huang's perspective

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

Their papers

• Dynamics of Deep Neural Networks and Neural Tangent Hierarchy (2019) — 170 citations
• Transition from Tracy–Widom to Gaussian fluctuations of extremal eigenvalues of sparse Erdős–Rényi graphs (2017) — 55 citations
• Dyson Brownian motion for general $$\beta $$ and potential at the edge (2018) — 51 citations
• Eigenvector Statistics of Sparse Random Matrices (2016) — 50 citations