Edward Y. Chang

Artificial Intelligence · with Wu · 2015–2019

A researcher in the Science corpus: 8 papers; trusts 204 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 60 citations into it
• Computer Vision and Pattern Recognition — 60 citations into it; #20,853 of 21,575 by trust here, #10,677 by citations
• Information Systems — 26 citations into it
• Generative Models — 21 citations into it; #1,900 of 1,956 by trust here, #1,796 by citations
• Representation & Self-Supervised Learning — 20 citations into it
• Management Science and Operations Research — 11 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Model Architectures — 8 citations into it

Whom Edward Y. Chang trusts overall

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

1. Geoffrey E. Hinton
2. Kai-Fu Tang
3. Chih-Jen Lin
4. Alex Krizhevsky
5. Igor Kononenko
6. Yoshua Bengio
7. Diederik P. Kingma
8. Richard S. Sutton
9. Kaiming He
10. Volodymyr Mnih

Who trusts Edward Y. Chang overall

1. Hao-Cheng Kao
2. Aleksandar Bojchevski
3. Chao Yu
4. Kai-Fu Tang
5. Daokun Zhang

Papers from Edward Y. Chang's perspective

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

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

Their papers

• RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes (2019) — 160 citations
• Context-Aware Symptom Checking for Disease Diagnosis Using Hierarchical Reinforcement Learning (2018) — 126 citations
• Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks (2018) — 541 citations
• Artificial Intelligence in XPRIZE DeepQ Tricorder (2017) — 15 citations
• DeepQ: Advancing Healthcare through Artificial Intelligence and Virtual Reality (2017) — 5 citations
• Transfer representation learning for medical image analysis (2015) — 136 citations
• Scalable Gaussian Process Regression Using Deep Neural Networks (2015) — 70 citations
• Network Representation Learning with Rich Text Information (2015) — 1,111 citations