Linqi Zhou

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 177 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 49 citations into it
• Generative Models — 37 citations into it; #949 of 1,956 by trust here, #1,021 by citations
• Computational Mechanics — 26 citations into it; #5,202 of 10,001 by trust here, #2,715 by citations
• Artificial Intelligence — 24 citations into it
• Probabilistic & Bayesian Methods — 19 citations into it
• Geology — 11 citations into it
• 3D Vision & Pose — 10 citations into it; #427 of 689 by trust here, #404 by citations
• Computer Graphics and Computer-Aided Design — 10 citations into it; #847 of 1,584 by trust here, #558 by citations

Whom Linqi Zhou trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Alex Krizhevsky
4. Yoshua Bengio
5. Yann LeCun
6. Kaiming He
7. Ilya Sutskever
8. Radford M. Neal
9. Ross B. Girshick
10. Charles Ruizhongtai Qi

Who trusts Linqi Zhou overall

1. Chin-Wei Huang
2. Stanislaw Szymanowicz
3. Rui Chen
4. Florinel-Alin Croitoru
5. Ajay Jain
6. Alex Nichol
7. Kevin Black
8. Chaozheng Wu
9. Arash Vahdat
10. Xiaohui Zeng

Papers from Linqi Zhou's perspective

Ordered by how strongly the researchers Linqi Zhou 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. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Joint Training of Variational Auto-Encoder and Latent Energy-Based Model (2020) — 63 citations
• 3D Shape Generation and Completion through Point-Voxel Diffusion (2021) — 707 citations