Seoyoon Kim

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Graph Learning — 8 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Seoyoon Kim trusts overall

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

1. Geoffrey E. Hinton
2. Stephen Grossberg
3. Jeffrey Scott Vitter
4. Arslan Chaudhry
5. Thomas Kipf
6. Yoshua Bengio
7. Max Welling
8. Zhizhong Li
9. Alex Krizhevsky
10. Diederik P. Kingma

Papers from Seoyoon Kim's perspective

Ordered by how strongly the researchers Seoyoon Kim 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• DyGRAIN: An Incremental Learning Framework for Dynamic Graphs (2022) — 39 citations