Qinsheng Zhang

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 403 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 108 citations into it; #6,545 of 21,575 by trust here, #5,843 by citations
• Generative Models — 100 citations into it; #493 of 1,956 by trust here, #602 by citations
• Artificial Intelligence — 63 citations into it; #12,002 of 35,345 by trust here, #18,186 by citations
• Statistical and Nonlinear Physics — 29 citations into it; #2,585 of 10,127 by trust here, #3,735 by citations
• Probabilistic & Bayesian Methods — 21 citations into it
• Signal Processing — 16 citations into it
• Biophysics — 10 citations into it
• Computational Mechanics — 9 citations into it

Whom Qinsheng Zhang trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Yang Song
4. Geoffrey E. Hinton
5. Jonathan Ho
6. Yann LeCun
7. Pascal Vincent
8. Yoshua Bengio
9. Alex Nichol
10. Prafulla Dhariwal

Who trusts Qinsheng Zhang overall

1. Axel Sauer
2. Ling Yang
3. Xinyin Ma
4. Ye Yuan
5. Wenliang Zhao
6. Hanqun Cao
7. Cheng Lu
8. Tianwei Yin
9. Neta Shaul
10. Songwei Ge

Papers from Qinsheng Zhang's perspective

Ordered by how strongly the researchers Qinsheng Zhang 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers (2022) — 1,087 citations
• Fast Sampling of Diffusion Models with Exponential Integrator (2022) — 629 citations
• Diffusion Normalizing Flow (2021) — 118 citations