Jiangwei Xie

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 405 researchers and is trusted by 49 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it; #5,012 of 35,345 by trust here, #8,525 by citations
• Computer Vision and Pattern Recognition — 74 citations into it; #4,618 of 21,575 by trust here, #6,426 by citations
• Meta & Continual Learning — 47 citations into it; #109 of 1,041 by trust here, #231 by citations
• Representation & Self-Supervised Learning — 26 citations into it; #689 of 3,145 by trust here, #1,277 by citations
• Radiology, Nuclear Medicine and Imaging — 16 citations into it
• Optimization & Training — 11 citations into it
• Efficiency & Compression — 7 citations into it
• Model Architectures — 7 citations into it

Whom Jiangwei Xie trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Yann LeCun
6. Diederik P. Kingma
7. Ross B. Girshick
8. Ilya Sutskever
9. X. Zhang
10. Shaoqing Ren

Who trusts Jiangwei Xie overall

1. Da-Wei Zhou
2. Gyuhak Kim
3. Yabin Wang
4. Shipeng Yan
5. Han-Jia Ye
6. Liyuan Wang
7. Liangzu Peng
8. Fu-Yun Wang
9. De-chuan Zhan
10. Qiwen Wang

Papers from Jiangwei Xie's perspective

Ordered by how strongly the researchers Jiangwei Xie 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. Learning Multiple Layers of Features from Tiny Images
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• DER: Dynamically Expandable Representation for Class Incremental Learning (2021) — 671 citations
• An EM Framework for Online Incremental Learning of Semantic Segmentation (2021) — 45 citations
• General Incremental Learning with Domain-aware Categorical Representations (2022) — 50 citations