Zhongzhi Yu
Artificial Intelligence · 2020
A researcher in the Science corpus: 1 paper; trusts 115 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it
- Reinforcement Learning — 46 citations into it
- Computer Vision and Pattern Recognition — 28 citations into it
- Electrical and Electronic Engineering — 9 citations into it
- Efficiency & Compression — 8 citations into it
- Model Architectures — 8 citations into it
- Optimization & Training — 8 citations into it
- Control and Systems Engineering — 7 citations into it
Whom Zhongzhi Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Quoc V. Le
- J. Urgen Schmidhuber
- Diederik P. Kingma
- Yann LeCun
- Barret Zoph
Papers from Zhongzhi Yu's perspective
Ordered by how strongly the researchers Zhongzhi Yu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- 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)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)