Yang Lu
Artificial Intelligence · Journal of Industrial Information Integration · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 40 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 55 citations into it
- Information Systems — 54 citations into it; #3,790 of 8,771 by trust here, #7,107 by citations
- Computer Networks and Communications — 40 citations into it; #4,570 of 9,886 by trust here, #7,832 by citations
- Industrial and Manufacturing Engineering — 22 citations into it; #61 of 2,521 by trust here, #381 by citations
- Computer Vision and Pattern Recognition — 20 citations into it
- Management Information Systems — 10 citations into it; #102 of 3,376 by trust here, #316 by citations
- Representation & Self-Supervised Learning — 7 citations into it
- Signal Processing — 7 citations into it
Whom Yang Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Lida Xu
- Alex Krizhevsky
- Yann LeCun
- Ruslan Salakhutdinov
- Alex Graves
- Li Deng
- Hugo Larochelle
Who trusts Yang Lu overall
- Sven Winkelhaus
- Angira Sharma
- Miguel Núñez-Merino
- Guilherme Luz Tortorella
- Ana Beatriz Lopes de Sousa Jabbour
- Foivos Psarommatis
- Ling Xia Li
- Lida Xu
- Eric H. Grosse
- Amr Adel
Papers from Yang Lu's perspective
Ordered by how strongly the researchers Yang Lu 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- The blockchain: State-of-the-art and research challenges (2019) — 458 citations
- Artificial intelligence: a survey on evolution, models, applications and future trends (2019) — 555 citations
- Industry 4.0: A survey on technologies, applications and open research issues (2017) — 2,569 citations