Soonwon Hong

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Meta & Continual Learning — 16 citations into it
• Optimization & Training — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Soonwon Hong trusts overall

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

1. Alex Krizhevsky
2. Max Welling
3. Sergey Ioffe
4. Geoffrey E. Hinton
5. Kaiming He
6. Christian Szegedy
7. Jia Deng
8. Zhizhong Li
9. Diederik P. Kingma
10. Yoshua Bengio

Papers from Soonwon Hong's perspective

Ordered by how strongly the researchers Soonwon Hong 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. Learning Multiple Layers of Features from Tiny Images
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Long Short-Term Memory

Their papers

• Task-Balanced Batch Normalization for Exemplar-based Class-Incremental Learning (2022) — 3 citations