Youngmin Oh

Artificial Intelligence · 2022

A researcher in the Science corpus: 2 papers; trusts 222 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it
• Reinforcement Learning — 35 citations into it
• Computer Vision and Pattern Recognition — 30 citations into it
• Meta & Continual Learning — 21 citations into it
• Management Science and Operations Research — 11 citations into it
• Computational Theory and Mathematics — 9 citations into it
• Optimization & Training — 8 citations into it
• Electrical and Electronic Engineering — 7 citations into it

Whom Youngmin Oh trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Richard S. Sutton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Diederik P. Kingma
7. Yann LeCun
8. Ilya Sutskever
9. Ross B. Girshick
10. Pieter Abbeel

Who trusts Youngmin Oh overall

1. Da-Wei Zhou
2. Liyuan Wang
3. Qiwen Wang
4. Xingxing Zhang

Papers from Youngmin Oh's perspective

Ordered by how strongly the researchers Youngmin Oh 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
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

• ALIFE: Adaptive Logit Regularizer and Feature Replay for Incremental Semantic Segmentation (2022) — 50 citations
• Model-augmented Prioritized Experience Replay (2022) — 22 citations