Li Zhang

Artificial Intelligence · with Jiang · 2018

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Model Architectures — 7 citations into it
• Optimization & Training — 7 citations into it

Whom Li Zhang trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Paul J. Werbos (in Optimization & Training)
2. Diederik P. Kingma (in Artificial Intelligence)
3. Jimmy Ba (in Artificial Intelligence)
4. Christian Szegedy (in Artificial Intelligence)
5. Sergey Ioffe (in Artificial Intelligence)

Papers from Li Zhang's perspective

Ordered by how strongly the researchers Li Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Long Short-Term Memory
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Dropout: a simple way to prevent neural networks from overfitting
5. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
6. Backpropagation Through Time: What It Does and How to Do It
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. ImageNet classification with deep convolutional neural networks
9. Recurrent nets that time and count
10. Gradient-based learning applied to document recognition

Their papers

• LSTM-Based EEG Classification in Motor Imagery Tasks (2018) — 322 citations