Raehyun Kim

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Graph Learning — 27 citations into it
• Statistical and Nonlinear Physics — 13 citations into it
• Molecular Biology — 7 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Raehyun Kim trusts overall

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

1. Thomas Kipf
2. Max Welling
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoshua Bengio
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Aditya Grover
9. Jure Leskovec
10. William L. Hamilton

Papers from Raehyun Kim's perspective

Ordered by how strongly the researchers Raehyun Kim 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Et al
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Graph Transformer Networks (2019) — 1,382 citations