Kelong Mao

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Information Systems — 13 citations into it
• Graph Learning — 11 citations into it

Whom Kelong Mao trusts overall

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

1. Xiangnan He
2. Xiang Wang
3. Ruining He
4. Yehuda Koren
5. Tomas Mikolov
6. Aditya Grover
7. Steffen Rendle
8. Geoffrey E. Hinton
9. Ilya Sutskever
10. Bryan Perozzi

Papers from Kelong Mao's perspective

Ordered by how strongly the researchers Kelong Mao 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation (2021) — 471 citations