Minghao Guo

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 357 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it
• Computer Vision and Pattern Recognition — 84 citations into it
• Model Architectures — 34 citations into it
• Optimization & Training — 24 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Neural Architecture Search & AutoML — 17 citations into it
• Efficiency & Compression — 9 citations into it
• Reinforcement Learning — 9 citations into it

Whom Minghao Guo trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Barret Zoph
4. Geoffrey E. Hinton
5. Karen Simonyan
6. Quoc V. Le
7. Ross B. Girshick
8. Yoshua Bengio
9. Ronald J. Williams
10. Yann LeCun

Who trusts Minghao Guo overall

1. Pouya Bashivan
2. Miao Zhang
3. Tianyu Pang
4. Yao-Yuan Yang
5. Peiwen Lin
6. Pengzhen Ren
7. Yuan Gao
8. Chen Lin
9. Xiaojun Chang
10. Mark Tensen

Papers from Minghao Guo's perspective

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

Their papers

• When NAS Meets Robustness: In Search of Robust Architectures Against Adversarial Attacks (2019) — 178 citations
• IRLAS: Inverse Reinforcement Learning for Architecture Search (2018) — 43 citations
• Online Hyper-Parameter Learning for Auto-Augmentation Strategy (2019) — 93 citations