Yabin Wang

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 2 papers; trusts 486 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 119 citations into it; #10,667 of 21,575 by trust here, #15,955 by citations
• Artificial Intelligence — 106 citations into it; #16,821 of 35,345 by trust here, #25,809 by citations
• Meta & Continual Learning — 65 citations into it; #511 of 1,041 by trust here, #897 by citations
• Representation & Self-Supervised Learning — 26 citations into it
• Radiology, Nuclear Medicine and Imaging — 17 citations into it
• Model Architectures — 11 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Prompting & Reasoning — 7 citations into it; #112 of 359 by trust here, #327 by citations

Whom Yabin Wang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Diederik P. Kingma
5. Yoshua Bengio
6. Marc'Aurelio Ranzato
7. Yann LeCun
8. Arslan Chaudhry
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Yabin Wang overall

1. Da-Wei Zhou
2. Yan-Shuo Liang
3. Liyuan Wang
4. Qiwen Wang
5. Han-Jia Ye
6. Doyoung Kim
7. James Smith
8. Wu-Jun Li
9. De-chuan Zhan
10. Xingxing Zhang

Papers from Yabin Wang's perspective

Ordered by how strongly the researchers Yabin Wang 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning (2022) — 371 citations
• A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials (2022) — 87 citations