Jihwan Jeong

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 4 papers; trusts 369 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 170 citations into it; #20,223 of 35,345 by trust here, #9,275 by citations
• Computer Vision and Pattern Recognition — 145 citations into it
• Meta & Continual Learning — 120 citations into it; #641 of 1,041 by trust here, #266 by citations
• Representation & Self-Supervised Learning — 62 citations into it
• Optimization & Training — 19 citations into it
• Reinforcement Learning — 19 citations into it
• Radiology, Nuclear Medicine and Imaging — 14 citations into it
• Evaluation & Benchmarks — 11 citations into it

Whom Jihwan Jeong trusts overall

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

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

Who trusts Jihwan Jeong overall

1. Gobinda Saha
2. Zheda Mai
3. Yiduo Guo
4. Hongwei Yan
5. Jiangpeng He
6. Gabriele Merlin
7. Lucas Caccia
8. Yaqian Zhang

Papers from Jihwan Jeong's perspective

Ordered by how strongly the researchers Jihwan 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
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

• Online Continual Learning in Image Classification: An Empirical Survey (2021) — 526 citations
• Batch-level Experience Replay with Review for Continual Learning (2020) — 18 citations
• Online Class-Incremental Continual Learning with Adversarial Shapley Value (2020) — 267 citations
• Adversarial Shapley Value Experience Replay for Task-Free Continual Learning (2020) — 6 citations