Xu Ji

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 466 researchers and is trusted by 87 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 100 citations into it; #3,681 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 78 citations into it; #10,940 of 35,345 by trust here, #10,566 by citations
• Representation & Self-Supervised Learning — 48 citations into it; #872 of 3,145 by trust here, #1,220 by citations
• Cognitive Neuroscience — 22 citations into it
• Meta & Continual Learning — 21 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 9 citations into it
• Media Technology — 7 citations into it

Whom Xu Ji 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. Kaiming He
6. Ross B. Girshick
7. Yann LeCun
8. Karen Simonyan
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Xu Ji overall

1. Ishan Misra
2. Yuki M. Asano
3. R. Devon Hjelm
4. Yonglong Tian
5. Lucas Caccia
6. Andrea Vedaldi
7. Pedro Morgado
8. Chunyuan Li
9. Christian Rupprecht
10. Dan Hendrycks

Papers from Xu Ji's perspective

Ordered by how strongly the researchers Xu Ji trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
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. Learning Multiple Layers of Features from Tiny Images

Their papers

• Invariant Information Clustering for Unsupervised Image Classification and Segmentation (2018) — 981 citations
• Automatic Recall Machines: Internal Replay, Continual Learning and the Brain (2020) — 11 citations
• On the role of neurogenesis in overcoming catastrophic forgetting (2018) — 15 citations
• Invariant Information Distillation for Unsupervised Image Segmentation and Clustering (2018) — 69 citations