Ziwei Zhang

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 4 papers; trusts 197 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 144 citations into it; #8,996 of 35,345 by trust here, #6,569 by citations
• Graph Learning — 105 citations into it; #338 of 693 by trust here, #291 by citations
• Computer Vision and Pattern Recognition — 83 citations into it; #9,923 of 21,575 by trust here, #8,296 by citations
• Statistical and Nonlinear Physics — 43 citations into it; #1,954 of 10,127 by trust here, #906 by citations
• Representation & Self-Supervised Learning — 33 citations into it; #1,688 of 3,145 by trust here, #1,527 by citations
• Model Architectures — 22 citations into it
• Molecular Biology — 20 citations into it
• Information Systems — 16 citations into it

Whom Ziwei Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Diederik P. Kingma
4. Yoshua Bengio
5. Alex Krizhevsky
6. Yann LeCun
7. Thomas Kipf
8. Max Welling
9. Ilya Sutskever
10. Jimmy Ba

Who trusts Ziwei Zhang overall

1. Marinka Zitnik
2. Guohao Li
3. Zhangyang Gao
4. Alaa Bessadok
5. Susheel Suresh
6. Saeed Rahmani
7. Fangda Gu
8. Uzair Aslam Bhatti
9. Mohammad Mustafa Taye
10. Xiao Wang

Papers from Ziwei Zhang's perspective

Ordered by how strongly the researchers Ziwei 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep Learning on Graphs: A Survey (2018) — 1,598 citations
• Asymmetric Transitivity Preserving Graph Embedding (2016) — 1,319 citations
• Robust Graph Convolutional Networks Against Adversarial Attacks (2019) — 559 citations
• Dense Relation Network: Learning Consistent and Context-Aware Representation for Semantic Image Segmentation (2018) — 42 citations