Xifeng Guo

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 158 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 38 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Model Architectures — 10 citations into it
• Optimization & Training — 8 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Xifeng Guo trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yann LeCun
4. Radford M. Neal
5. Yoshua Bengio
6. Alex Krizhevsky
7. L. Eon Bottou
8. Ross B. Girshick
9. Kaiming He
10. Jimmy Ba

Who trusts Xifeng Guo overall

1. Ava Vali
2. Yunfan Li
3. Yanbei Chen
4. Chun Wang
5. Xu Yang
6. Yihan Wu
7. Deyu Bo
8. Yue Liu
9. Xinwang Liu
10. S. M. Mousavi

Papers from Xifeng Guo's perspective

Ordered by how strongly the researchers Xifeng Guo 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Improved Deep Embedded Clustering with Local Structure Preservation (2017) — 1,034 citations
• A Survey of Clustering With Deep Learning: From the Perspective of Network Architecture (2018) — 507 citations
• Deep Clustering with Convolutional Autoencoders (2017) — 538 citations