Dong-Jun Han

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 2 papers; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Meta & Continual Learning — 25 citations into it
• Optimization & Training — 19 citations into it
• Computational Mechanics — 8 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Dong-Jun Han trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Oriol Vinyals
5. Yoshua Bengio
6. Diederik P. Kingma
7. Yann LeCun
8. Da-Wei Zhou
9. Jeremy Bernstein
10. Ross B. Girshick

Who trusts Dong-Jun Han overall

1. Keon-Hee Park

Papers from Dong-Jun Han's perspective

Ordered by how strongly the researchers Dong-Jun Han 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning (2023) — 75 citations
• Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks (2019) — 41 citations