Yangyang Shi

Artificial Intelligence · 2006–2019

A researcher in the Science corpus: 6 papers; trusts 47 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it; #14,303 of 35,345 by trust here, #8,525 by citations
• Natural Language Processing — 65 citations into it; #2,667 of 5,688 by trust here, #2,132 by citations
• Large Language Models — 22 citations into it
• Model Architectures — 22 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Optimization & Training — 9 citations into it
• Signal Processing — 9 citations into it
• Materials Chemistry — 8 citations into it; #11,184 of 11,513 by trust here, #6,536 by citations

Whom Yangyang Shi trusts overall

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

1. Tomas Mikolov
2. Geoffrey E. Hinton
3. R. Rosenfeld
4. Yoshua Bengio
5. Stanley F. Chen
6. Ilya Sutskever
7. Alex Graves
8. Oriol Vinyals
9. Yann LeCun
10. Alex Krizhevsky

Who trusts Yangyang Shi overall

1. Jianping Gou
2. Chen Chen
3. Kaisheng Yao
4. Raj Nath Patel
5. Baosheng Yu
6. Van-Khanh Tran

Papers from Yangyang Shi's perspective

Ordered by how strongly the researchers Yangyang Shi 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Recurrent neural networks for language understanding (2013) — 328 citations
• Spoken language understanding using long short-term memory neural networks (2014) — 308 citations
• Recurrent neural network language model adaptation with curriculum learning (2015) — 75 citations
• A Tin‐Based Amorphous Oxide Composite with a Porous, Spherical, Multideck‐Cage Morphology as a Highly Reversible Anode Material for Lithium‐Ion Batteries (2007) — 319 citations
• Knowledge Distillation for Recurrent Neural Network Language Modeling with Trust Regularization (2019) — 27 citations
• Highly Ordered Mesoporous Silicon Carbide Ceramics with Large Surface Areas and High Stability (2006) — 186 citations