Yan Yang

Artificial Intelligence · IEEE Transactions on Knowledge and Data Engineering · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 115 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 94 citations into it; #15,806 of 35,345 by trust here, #25,040 by citations
• Computer Vision and Pattern Recognition — 69 citations into it; #17,660 of 21,575 by trust here, #20,271 by citations
• Representation & Self-Supervised Learning — 21 citations into it; #2,064 of 3,145 by trust here, #2,863 by citations
• Natural Language Processing — 16 citations into it
• Computational Mechanics — 13 citations into it
• Signal Processing — 13 citations into it
• Media Technology — 12 citations into it; #2,866 of 3,621 by trust here, #3,522 by citations
• Meta & Continual Learning — 9 citations into it

Whom Yan Yang trusts overall

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

1. Feiping Nie
2. Yu Zheng
3. Steffen Bickel
4. Geoffrey E. Hinton
5. Jing Gao
6. Alex Krizhevsky
7. Sanjoy Dasgupta
8. Yoshua Bengio
9. V. P. Pauca
10. Ilya Sutskever

Who trusts Yan Yang overall

1. Zixuan Ke
2. Erlin Pan
3. Hao Wang
4. Bing Liu

Papers from Yan Yang's perspective

Ordered by how strongly the researchers Yan Yang 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
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. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multivariate time series forecasting via attention-based encoder-decoder framework (2020) — 412 citations
• GMC: Graph-Based Multi-View Clustering (2020) — 805 citations
• Forward and Backward Knowledge Transfer for Sentiment Classification (2019) — 18 citations
• A study of graph-based system for multi-view clustering (2019) — 339 citations
• Deep Air Quality Forecasting Using Hybrid Deep Learning Framework (2018) — 423 citations
• Multi-view clustering: A survey (2018) — 436 citations