Enoch Yeung
Statistical and Nonlinear Physics · 2017
A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 10 citations into it; #4,530 of 10,127 by trust here, #6,727 by citations
- Computational Mechanics — 8 citations into it; #4,836 of 10,001 by trust here, #6,877 by citations
- Artificial Intelligence — 7 citations into it
Whom Enoch Yeung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Igor Mezi'c
- Clarence W. Rowley
- Steven L. Brunton
- Joshua L. Proctor
- Bryan C. Daniels
- Samuel E. Otto
- Matthew O. Williams
- Naoya Takeishi
- Qianxao Li
- J. Nathan Kutz
Who trusts Enoch Yeung overall
- Jared D. Willard
- Naoya Takeishi
- Xiaowei Jia
- Shaoming Xu
- Yoshinobu Kawahara
- Michael S. Steinbach
- Ricardo Vinuesa
Papers from Enoch Yeung's perspective
Ordered by how strongly the researchers Enoch Yeung trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Dropout: a simple way to prevent neural networks from overfitting
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)