Tao Luo
Artificial Intelligence · with Ma · 2019
A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 40 citations into it; #26,707 of 35,345 by trust here, #19,018 by citations
- Scaling & Learning Theory — 29 citations into it; #326 of 428 by trust here, #303 by citations
- Optimization & Training — 19 citations into it; #2,121 of 2,601 by trust here, #1,661 by citations
- Statistical Learning Theory — 13 citations into it
- Model Architectures — 5 citations into it
Whom Tao Luo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Zhi-Qin John Xu
- George V. Cybenko
- Jimmy Ba
- Peter L. Bartlett
- Geoffrey E. Hinton
- Lénaïc Chizat
- Yann LeCun
- Yoshua Bengio
- Alex Krizhevsky
Who trusts Tao Luo overall
Papers from Tao Luo's perspective
Ordered by how strongly the researchers Tao Luo trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Understanding deep learning requires rethinking generalization
Their papers
- Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks (2019) — 776 citations
- A type of generalization error induced by initialization in deep neural networks (2019) — 54 citations