Chenchen Liu

Artificial Intelligence · with Chen · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Optimization & Training — 13 citations into it
• Scaling & Learning Theory — 9 citations into it

Whom Chenchen Liu trusts overall

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

1. Ian J. Goodfellow
2. James Martens
3. Christian Szegedy
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Oriol Vinyals
7. Yann LeCun
8. Alex Krizhevsky
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Chenchen Liu overall

1. Anqi Mao
2. Dongxian Wu

Papers from Chenchen Liu's perspective

Ordered by how strongly the researchers Chenchen Liu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Interpreting and Evaluating Neural Network Robustness (2019) — 59 citations
• Interpreting Adversarial Robustness: A View from Decision Surface in Input Space (2018) — 30 citations