Jinseo Jeong

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 521 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 135 citations into it; #18,091 of 35,345 by trust here, #16,771 by citations
• Computer Vision and Pattern Recognition — 102 citations into it
• Representation & Self-Supervised Learning — 38 citations into it
• Meta & Continual Learning — 32 citations into it; #548 of 1,041 by trust here, #613 by citations
• Optimization & Training — 31 citations into it
• Reinforcement Learning — 15 citations into it
• Safety, Robustness & Interpretability — 9 citations into it
• Civil and Structural Engineering — 7 citations into it

Whom Jinseo Jeong trusts overall

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

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

Who trusts Jinseo Jeong overall

1. Haiyan Yin
2. Matthias De Lange
3. Zheda Mai
4. Liyuan Wang
5. Da-Wei Zhou
6. Quang Pham
7. Mingfu Liang
8. Chris Dongjoo Kim

Papers from Jinseo Jeong's perspective

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

Their papers

• Continual Learning on Noisy Data Streams via Self-Purified Replay (2021) — 58 citations
• Imbalanced Continual Learning with Partitioning Reservoir Sampling (2020) — 136 citations