Zhongfei Zhang

Computer Vision and Pattern Recognition · 2013–2019

A researcher in the Science corpus: 12 papers; trusts 639 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 226 citations into it; #14,778 of 21,575 by trust here, #8,021 by citations
• Artificial Intelligence — 178 citations into it; #13,548 of 35,345 by trust here, #9,557 by citations
• Representation & Self-Supervised Learning — 76 citations into it; #2,204 of 3,145 by trust here, #1,741 by citations
• Natural Language Processing — 52 citations into it
• Model Architectures — 35 citations into it
• Multimodal Learning — 30 citations into it
• Probabilistic & Bayesian Methods — 27 citations into it
• Statistics and Probability — 25 citations into it

Whom Zhongfei Zhang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Krizhevsky
4. Ruslan Salakhutdinov
5. Ilya Sutskever
6. Radford M. Neal
7. Diederik P. Kingma
8. Yann LeCun
9. Kaiming He
10. Alex Graves

Who trusts Zhongfei Zhang overall

1. Yu Cheng
2. Chuhan Wu
3. Houssam Zenati

Papers from Zhongfei Zhang's perspective

Ordered by how strongly the researchers Zhongfei 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• A survey of appearance models in visual object tracking (2013) — 771 citations
• Deep Structured Energy Based Models for Anomaly Detection (2016) — 463 citations
• Doubly Convolutional Neural Networks (2016) — 66 citations
• A Survey of Multi-View Representation Learning (2016) — 640 citations
• Dropout Training of Matrix Factorization and Autoencoder for Link Prediction in Sparse Graphs (2015) — 38 citations
• Fine-tune BERT with Sparse Self-Attention Mechanism (2019) — 73 citations
• Self-Paced Boost Learning for Classification (2016) — 78 citations
• Learning of Multimodal Representations With Random Walks on the Click Graph (2016) — 47 citations
• DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks (2016) — 120 citations
• Structured Embedding via Pairwise Relations and Long-Range Interactions in Knowledge Base (2015) — 14 citations
• Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian Model (2013) — 23 citations
• Ieee Transactions on Knowledge and Data Engineering Context-aware Hypergraph Construction for Robust Spectral Clustering