Kijung Yoon

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Optimization & Training — 13 citations into it
• Model Architectures — 10 citations into it
• Natural Language Processing — 5 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it

Whom Kijung Yoon trusts overall

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

1. Diederik P. Kingma
2. Tom Minka
3. Geoffrey E. Hinton
4. Jimmy Ba
5. Yoshua Bengio
6. Kyunghyun Cho
7. Yujia Li
8. Yann LeCun
9. Alex Krizhevsky
10. Ruslan Salakhutdinov

Papers from Kijung Yoon's perspective

Ordered by how strongly the researchers Kijung Yoon trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Inference in Probabilistic Graphical Models by Graph Neural Networks (2018) — 110 citations
• Reviving and Improving Recurrent Back-Propagation (2018) — 140 citations