Bo Zhang

Artificial Intelligence · with Li · 2017–2025

A researcher in the Science corpus: 3 papers; trusts 191 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 88 citations into it
• Computer Vision and Pattern Recognition — 86 citations into it; #20,338 of 21,575 by trust here, #9,079 by citations
• Generative Models — 56 citations into it; #1,906 of 1,956 by trust here, #1,054 by citations
• Representation & Self-Supervised Learning — 29 citations into it
• Optimization & Training — 14 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Model Architectures — 8 citations into it

Whom Bo Zhang trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ronald J. Williams
6. Yann LeCun
7. Ilya Sutskever
8. Kaiming He
9. Ian J. Goodfellow
10. Jimmy Ba

Who trusts Bo Zhang overall

1. Jun Zhu

Papers from Bo Zhang's perspective

Ordered by how strongly the researchers Bo Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Triple Generative Adversarial Nets (2017) — 475 citations
• Jailbreaking LLMs' Safeguard with Universal Magic Words for Text Embedding Models (2025)
• Triple Generative Adversarial Networks (2019) — 57 citations