Ying Sha

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 44 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #24,491 of 35,345 by trust here, #33,294 by citations
• Natural Language Processing — 8 citations into it
• Health Information Management — 6 citations into it
• Model Architectures — 6 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Ying Sha trusts overall

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

1. Yoshua Bengio
2. Kyunghyun Cho
3. Dzmitry Bahdanau
4. Sepp Hochreiter
5. Tomas Mikolov
6. Geoffrey E. Hinton
7. Andrej Karpathy
8. Alex Krizhevsky
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Ying Sha overall

1. Tian Bai
2. Shanshan Zhang
3. Amitojdeep Singh
4. Brian L. Egleston

Papers from Ying Sha's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Interpretable Predictions of Clinical Outcomes with An Attention-based Recurrent Neural Network (2017) — 103 citations