Honghua Dong

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 70 citations into it
• Reinforcement Learning — 41 citations into it
• Natural Language Processing — 29 citations into it
• Computer Vision and Pattern Recognition — 23 citations into it
• Model Architectures — 11 citations into it

Whom Honghua Dong trusts overall

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

1. Ronald J. Williams
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Alex Graves
5. Yoshua Bengio
6. Alex Krizhevsky
7. Diederik P. Kingma
8. Yann LeCun
9. Richard S. Sutton
10. Kaiming He

Who trusts Honghua Dong overall

1. Zhengyao Jiang
2. A.S. d'Avila Garcez
3. Yufei Feng
4. Yatin Nandwani
5. Ofir Press
6. Denny Zhou
7. Shan Luo
8. Xinyun Chen

Papers from Honghua Dong's perspective

Ordered by how strongly the researchers Honghua Dong 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
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. GENERATIVE ADVERSARIAL NETS

Their papers

• Neural Logic Machines (2019) — 302 citations
• Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient (2019) — 348 citations