Joo-Kyung Kim
Artificial Intelligence · 2016–2018
A researcher in the Science corpus: 2 papers; trusts 52 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 36 citations into it
- Natural Language Processing — 17 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Model Architectures — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Joo-Kyung Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Sepp Hochreiter
- J. Urgen Schmidhuber
- Geoffrey E. Hinton
- Yoshua Bengio
- Yoon Kim
- Diederik P. Kingma
- Gökhan Tür
- Ilya Sutskever
- Jason Aaron Edward Weston
Who trusts Joo-Kyung Kim overall
Papers from Joo-Kyung Kim's perspective
Ordered by how strongly the researchers Joo-Kyung Kim trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)