Jian Zhang

Computer Vision and Pattern Recognition · with Ni · 2019

A researcher in the Science corpus: 3 papers; trusts 310 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 89 citations into it
• Artificial Intelligence — 87 citations into it
• Representation & Self-Supervised Learning — 41 citations into it
• Efficiency & Compression — 26 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 10 citations into it
• Generative Models — 7 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Jian Zhang trusts overall

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

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

Who trusts Jian Zhang overall

1. Yusuke Iwasawa
2. Divyat Mahajan

Papers from Jian Zhang's perspective

Ordered by how strongly the researchers Jian 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. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Adversarial Domain Adaptation with Domain Mixup (2019) — 509 citations
• Variational Few-Shot Learning (2019) — 168 citations
• Variational Convolutional Neural Network Pruning (2019) — 350 citations