Hua Shen
Artificial Intelligence · with Wang · 2016–2018
A researcher in the Science corpus: 2 papers; trusts 222 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 61 citations into it; #29,560 of 35,345 by trust here, #29,412 by citations
- Safety, Robustness & Interpretability — 46 citations into it; #1,871 of 2,251 by trust here, #2,110 by citations
- Computer Vision and Pattern Recognition — 35 citations into it
- Model Architectures — 11 citations into it
- Hardware and Architecture — 6 citations into it
Whom Hua Shen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Karen Simonyan
- Alex Krizhevsky
- Ilya Sutskever
- Yann LeCun
- Christian Szegedy
- Diederik P. Kingma
- Ian J. Goodfellow
Who trusts Hua Shen overall
Papers from Hua Shen's perspective
Ordered by how strongly the researchers Hua Shen 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Interpretable Deep Learning under Fire (2018) — 195 citations
- A Time Series Forecasting Model Based on Deep Learning Integrated Algorithm with Stacked Autoencoders and SVR for FX Prediction (2016) — 11 citations