Jaehoon Oh

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 124 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it
• Computer Vision and Pattern Recognition — 38 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Optimization & Training — 12 citations into it
• Federated & Distributed Learning — 11 citations into it
• Meta & Continual Learning — 5 citations into it

Whom Jaehoon Oh trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Yann LeCun
7. Ilya Sutskever
8. Ross B. Girshick
9. Xavier Glorot
10. X. Zhang

Papers from Jaehoon Oh's perspective

Ordered by how strongly the researchers Jaehoon 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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

• Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation (2021) — 337 citations
• FedBABU: Towards Enhanced Representation for Federated Image Classification (2021) — 355 citations