Yiren Zhao

Artificial Intelligence · 2018–2024

A researcher in the Science corpus: 7 papers; trusts 320 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 150 citations into it
• Computer Vision and Pattern Recognition — 113 citations into it
• Efficiency & Compression — 50 citations into it
• Model Architectures — 34 citations into it
• Safety, Robustness & Interpretability — 33 citations into it
• Optimization & Training — 23 citations into it
• Natural Language Processing — 20 citations into it
• Representation & Self-Supervised Learning — 17 citations into it

Whom Yiren Zhao trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. Ilya Sutskever
8. Karen Simonyan
9. Ross B. Girshick
10. Christian Szegedy

Who trusts Yiren Zhao overall

1. Weizhe Hua
2. Yang He
3. Ali Ehteshami Bejnordi
4. Ilia Shumailov
5. Changlin Li
6. Chuanjian Liu
7. Jinting Chen

Papers from Yiren Zhao's perspective

Ordered by how strongly the researchers Yiren 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Dynamic Channel Pruning: Feature Boosting and Suppression (2018) — 348 citations
• The Curse of Recursion: Training on Generated Data Makes Models Forget (2023) — 507 citations
• Sponge Examples: Energy-Latency Attacks on Neural Networks (2020) — 192 citations
• AI models collapse when trained on recursively generated data (2024) — 891 citations
• Manipulating SGD with Data Ordering Attacks (2021) — 122 citations
• Probabilistic Dual Network Architecture Search on Graphs (2020) — 27 citations
• Pay Attention to Features, Transfer Learn Faster CNNs (2020) — 83 citations