Dian Chen

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 283 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it
• Computer Vision and Pattern Recognition — 78 citations into it
• Reinforcement Learning — 48 citations into it
• Control and Systems Engineering — 39 citations into it; #6,608 of 8,257 by trust here, #536 by citations
• Representation & Self-Supervised Learning — 31 citations into it
• Aerospace Engineering — 10 citations into it; #6,228 of 6,421 by trust here, #1,815 by citations
• Automotive Engineering — 10 citations into it
• Optimization & Training — 10 citations into it

Whom Dian Chen trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yann LeCun
6. Christian Szegedy
7. Yoshua Bengio
8. Ross B. Girshick
9. Ilya Sutskever
10. Sergey Ioffe

Who trusts Dian Chen overall

1. Kashyap Chitta
2. Hao Shao
3. Aditya Prakash
4. Li Chen
5. Daniel Dauner
6. Andreas Geiger
7. Jemin Hwangbo
8. Ananye Agarwal
9. Ardi Tampuu
10. Zhejun Zhang

Papers from Dian Chen's perspective

Ordered by how strongly the researchers Dian Chen 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. 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. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Zero-Shot Visual Imitation (2018) — 329 citations
• Combining self-supervised learning and imitation for vision-based rope manipulation (2017) — 338 citations
• Contrastive Test-Time Adaptation (2022) — 401 citations
• Learning by Cheating (2019) — 689 citations