Qiwei Ye

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 2 papers; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 28 citations into it
• Artificial Intelligence — 23 citations into it
• Generative Models — 23 citations into it
• Optimization & Training — 10 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Statistical and Nonlinear Physics — 6 citations into it

Whom Qiwei Ye trusts overall

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

1. Alex Krizhevsky
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Kaiming He
5. Diederik P. Kingma
6. Yann LeCun
7. Takeru Miyato
8. Ilya Sutskever
9. Individualized Treat
10. Alex Graves

Who trusts Qiwei Ye overall

1. Minkai Xu

Papers from Qiwei Ye's perspective

Ordered by how strongly the researchers Qiwei Ye 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator (2020) — 8 citations
• LightGBM: A Highly Efficient Gradient Boosting Decision Tree (2017) — 15,550 citations