Yang Zhao

Artificial Intelligence · with Chen · 2019–2021

A researcher in the Science corpus: 7 papers; trusts 423 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 135 citations into it
• Computer Vision and Pattern Recognition — 92 citations into it
• Generative Models — 65 citations into it; #1,719 of 1,956 by trust here, #1,796 by citations
• Privacy & Security — 26 citations into it
• Probabilistic & Bayesian Methods — 20 citations into it
• Optimization & Training — 17 citations into it
• Statistics and Probability — 12 citations into it
• Representation & Self-Supervised Learning — 11 citations into it

Whom Yang Zhao trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Max Welling
5. Yoshua Bengio
6. Kaiming He
7. Tero Karras
8. Yann LeCun
9. Jia Deng
10. Ilya Sutskever

Who trusts Yang Zhao overall

1. Dinh C. Nguyen
2. K. J. Joseph
3. Jongheon Jeong
4. Terrance Devries
5. Lichao Sun
6. Ming Ding
7. Tian Li
8. Jihong Park
9. Ahmed Imteaj
10. Lingjuan Lyu

Papers from Yang Zhao's perspective

Ordered by how strongly the researchers Yang Zhao 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. 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. GENERATIVE ADVERSARIAL NETS

Their papers

• Local Differential Privacy-Based Federated Learning for Internet of Things (2020) — 414 citations
• Mobile Edge Computing, Blockchain and Reputation-based Crowdsourcing IoT Federated Learning: A Secure, Decentralized and Privacy-preserving System (2019) — 113 citations
• Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling (2021) — 52 citations
• Unpaired Image-to-Image Translation via Latent Energy Transport (2020) — 31 citations
• Feature Quantization Improves GAN Training (2020) — 50 citations
• Bayesian Meta Sampling for Fast Uncertainty Adaptation (2020) — 13 citations
• Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices (2019) — 508 citations