Xinbang Zhang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 480 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 194 citations into it
• Computer Vision and Pattern Recognition — 184 citations into it
• Model Architectures — 74 citations into it
• Neural Architecture Search & AutoML — 59 citations into it
• Optimization & Training — 42 citations into it
• Efficiency & Compression — 39 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Neurology — 9 citations into it

Whom Xinbang Zhang trusts overall

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

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

Who trusts Xinbang Zhang overall

1. Jiahua Dong
2. Zichao Guo
3. Asaf Noy
4. Bin Liu
5. Lixu Wang
6. Zhen Fang
7. Niv Nayman

Papers from Xinbang Zhang's perspective

Ordered by how strongly the researchers Xinbang Zhang 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization (2018) — 100 citations
• Differentiable Architecture Search with Ensemble Gumbel-Softmax (2019) — 20 citations
• DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling (2020) — 15 citations
• EAT-NAS: elastic architecture transfer for accelerating large-scale neural architecture search (2019) — 25 citations
• DATA: Differentiable ArchiTecture Approximation (2019) — 56 citations