Ailing Zeng

Computer Vision and Pattern Recognition · 2021–2023

A researcher in the Science corpus: 5 papers; trusts 253 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 87 citations into it
• Artificial Intelligence — 62 citations into it; #19,627 of 35,345 by trust here, #19,018 by citations
• Signal Processing — 42 citations into it; #2,667 of 7,572 by trust here, #2,589 by citations
• Management Science and Operations Research — 32 citations into it
• Model Architectures — 22 citations into it
• Human-Computer Interaction — 17 citations into it
• Time-Series & Forecasting — 16 citations into it
• 3D Vision & Pose — 10 citations into it

Whom Ailing Zeng trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Kaiming He
5. Alex Krizhevsky
6. Dzmitry Bahdanau
7. Yann LeCun
8. Ilya Sutskever
9. Haixu Wu
10. Ross B. Girshick

Who trusts Ailing Zeng overall

1. Zhijian Xu
2. Donghao Luo
3. Shiyu Wang
4. Yunhao Zhang
5. Gerald Woo
6. Nate Gruver
7. Yuqi Nie
8. Haixu Wu
9. Vijayabharathi Ekambaram
10. Si Chen

Papers from Ailing Zeng's perspective

Ordered by how strongly the researchers Ailing Zeng 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction (2021) — 851 citations
• Effective Whole-body Pose Estimation with Two-stages Distillation (2023) — 405 citations
• FITS: Modeling Time Series with 10k Parameters (2023) — 306 citations
• Are Transformers Effective for Time Series Forecasting? (2022) — 4,138 citations
• Human Pose Regression with Residual Log-likelihood Estimation (2021) — 300 citations