Zhen Zhang

Artificial Intelligence · with Jin · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Computer Vision and Pattern Recognition — 37 citations into it
• Efficiency & Compression — 22 citations into it
• Optimization & Training — 22 citations into it
• Hardware and Architecture — 19 citations into it
• Computer Networks and Communications — 16 citations into it
• ML Systems & Hardware — 13 citations into it
• Information Systems — 9 citations into it

Whom Zhen Zhang trusts overall

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

1. Jacob Devlin
2. Kaiming He
3. Geoffrey E. Hinton
4. Alexander Sergeev
5. Sergey Zagoruyko
6. D. Narayanan
7. Alex Krizhevsky
8. Christian Szegedy
9. Samyam Rajbhandari
10. Alec Radford

Who trusts Zhen Zhang overall

1. Hong Zhang

Papers from Zhen Zhang's perspective

Ordered by how strongly the researchers Zhen 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud (2022) — 57 citations
• PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications (2020) — 156 citations