Zhitao Ying
Artificial Intelligence · 2017
A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 309 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 21 citations into it; #1,084 of 35,345 by trust here, #1,719 by citations
- Graph Learning — 20 citations into it; #11 of 693 by trust here, #32 by citations
- Representation & Self-Supervised Learning — 15 citations into it; #138 of 3,145 by trust here, #214 by citations
- Computer Vision and Pattern Recognition — 6 citations into it
- Molecular Biology — 6 citations into it; #60 of 17,773 by trust here, #858 by citations
- Natural Language Processing — 6 citations into it
Whom Zhitao Ying trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Thomas Kipf
- Omer Levy
- Aditya Grover
- Max Welling
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Jure Leskovec
Who trusts Zhitao Ying overall
- Jiaxuan You
- Rex Ying
- William L. Hamilton
- Jure Leskovec
- Petar Velickovic
- Xiang Wang
- Weihua Hu
- Xiao Wang
- Guohao Li
- Aleksandar Bojchevski
Papers from Zhitao Ying's perspective
Ordered by how strongly the researchers Zhitao Ying 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)
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Inductive Representation Learning on Large Graphs (2017) — 20,392 citations