Chao Xing
Computer Vision and Pattern Recognition · 2015–2016
A researcher in the Science corpus: 2 papers; trusts 56 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 32 citations into it
- Artificial Intelligence — 21 citations into it; #15,422 of 35,345 by trust here, #13,163 by citations
- Natural Language Processing — 13 citations into it; #2,792 of 5,688 by trust here, #3,053 by citations
- Representation & Self-Supervised Learning — 11 citations into it; #1,714 of 3,145 by trust here, #1,811 by citations
Whom Chao Xing trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Tomas Mikolov
- Ilya Sutskever
- Yoshua Bengio
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Diederik P. Kingma
- Quoc V. Le
- Ross B. Girshick
Who trusts Chao Xing overall
- Mikel Artetxe
- Viktor Hangya
- Dong Wang
- Gorka Labaka
- Sascha Rothe
- Yu-An Chung
- Mengzhou Xia
- Meng Zhang
- Samuel L. Smith
- Eneko Agirre
Papers from Chao Xing's perspective
Ordered by how strongly the researchers Chao Xing trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation (2015) — 431 citations
- Deep Label Distribution Learning With Label Ambiguity (2016) — 500 citations