Richard Wang

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Optimization & Training — 5 citations into it

Whom Richard Wang trusts overall

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

1. Diederik P. Kingma
2. Frances H. Arnold
3. Reuven Y. Rubinstein
4. Peter I. Frazier
5. Geoffrey E. Hinton
6. Kaiming He
7. Jimmy Ba
8. Alex Krizhevsky
9. Nikolaus Hansen
10. Yoshua Bengio

Papers from Richard Wang's perspective

Ordered by how strongly the researchers Richard Wang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. GENERATIVE ADVERSARIAL NETS
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• AdaLead: A simple and robust adaptive greedy search algorithm for sequence design (2020) — 113 citations
• MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation (2021) — 98 citations