Zhen Xu

Artificial Intelligence · with Dai · 2019

A researcher in the Science corpus: 3 papers; trusts 130 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Generative Models — 43 citations into it
• Optimization & Training — 30 citations into it
• Probabilistic & Bayesian Methods — 24 citations into it
• Model Architectures — 13 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Signal Processing — 9 citations into it

Whom Zhen Xu trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. John Schulman
8. X. Zhang
9. Ilya Sutskever
10. Jimmy Ba

Who trusts Zhen Xu overall

1. Luke Metz
2. C. Freeman

Papers from Zhen Xu's perspective

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

Their papers

• Flow Contrastive Estimation of Energy-Based Models (2019) — 129 citations
• Learning an Adaptive Learning Rate Schedule (2019) — 79 citations
• Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer (2019) — 301 citations