Cong Liu

Artificial Intelligence · with Zhang · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 46 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Efficiency & Compression — 12 citations into it
• Generative Models — 11 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Model Architectures — 7 citations into it

Whom Cong Liu trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Radford M. Neal
5. Alex Krizhevsky
6. Daniel Lowd
7. Karen Simonyan
8. Yoshua Bengio
9. Alex Graves
10. Yann LeCun

Papers from Cong Liu's perspective

Ordered by how strongly the researchers Cong Liu 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. Going deeper with convolutions
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• ILFO: Adversarial Attack on Adaptive Neural Networks (2020) — 41 citations
• DeepRoad: GAN-Based Metamorphic Testing and Input Validation Framework for Autonomous Driving Systems (2018) — 648 citations