Jong Jin Kim

Artificial Intelligence · 2021

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 — 20 citations into it
• Generative Models — 8 citations into it

Whom Jong Jin Kim trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton

Papers from Jong Jin Kim's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
5. ImageNet classification with deep convolutional neural networks
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Expressive Text-to-Speech Using Style Tag (2021) — 53 citations