Hai-Ning Liang

Artificial Intelligence · 2010–2015

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #17,131 of 35,345 by trust here, #19,873 by citations
• Computer Vision and Pattern Recognition — 11 citations into it
• Safety, Robustness & Interpretability — 9 citations into it; #1,129 of 2,251 by trust here, #1,673 by citations

Whom Hai-Ning Liang trusts overall

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

1. Eugene Garfield
2. Chaomei Chen
3. Alex Krizhevsky
4. Ian J. Goodfellow
5. Yann LeCun
6. Geoffrey E. Hinton
7. Yoshua Bengio
8. Christian Szegedy
9. Alhussein Fawzi
10. Ilya Sutskever

Who trusts Hai-Ning Liang overall

1. Lieven Billiet
2. Alexander Ororbia
3. Naveed Akhtar

Papers from Hai-Ning Liang's perspective

Ordered by how strongly the researchers Hai-Ning Liang trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• A Unified Gradient Regularization Family for Adversarial Examples (2015) — 221 citations
• Overview of the Health Informatics Research Field: A Bibliometric Approach (2010) — 12 citations