Yiwen Guo

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 5 papers; trusts 509 researchers and is trusted by 137 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 160 citations into it; #3,035 of 35,345 by trust here, #3,757 by citations
• Computer Vision and Pattern Recognition — 150 citations into it; #2,974 of 21,575 by trust here, #2,857 by citations
• Model Architectures — 59 citations into it
• Neural Architecture Search & AutoML — 46 citations into it
• Efficiency & Compression — 43 citations into it; #111 of 1,264 by trust here, #326 by citations
• Optimization & Training — 33 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Evolutionary Computation — 6 citations into it

Whom Yiwen Guo trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Kaiming He
5. Yoshua Bengio
6. Ilya Sutskever
7. Karen Simonyan
8. Christian Szegedy
9. Diederik P. Kingma
10. Quoc V. Le

Who trusts Yiwen Guo overall

1. Yang He
2. Aojun Zhou
3. Frederick Tung
4. Karim Ahmed
5. Arun Mallya
6. Georgios Georgiadis
7. Wujie Wen
8. Mark Sandler
9. Trevor Gale
10. Lorenzo Torresani

Papers from Yiwen Guo's perspective

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

Their papers

• Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights (2017) — 1,135 citations
• Dynamic Network Surgery for Efficient DNNs (2016) — 1,158 citations
• Differentiable Architecture Search with Ensemble Gumbel-Softmax (2019) — 20 citations
• DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling (2020) — 15 citations
• DATA: Differentiable ArchiTecture Approximation (2019) — 56 citations