Younggun Lee

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 64 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #22,753 of 35,345 by trust here, #22,463 by citations
• Speech & Audio — 19 citations into it
• Natural Language Processing — 16 citations into it
• Model Architectures — 11 citations into it
• Signal Processing — 10 citations into it; #4,710 of 7,572 by trust here, #4,750 by citations
• Computer Vision and Pattern Recognition — 9 citations into it

Whom Younggun Lee trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Ilya Sutskever
5. Kyunghyun Cho
6. Yuxuan Wang
7. Dzmitry Bahdanau
8. Alex Krizhevsky
9. Alex Graves
10. Sergey Ioffe

Who trusts Younggun Lee overall

1. Chenpeng Du
2. Rui Liu
3. Chung-Ming Chien
4. Yinjiao Lei
5. Takuma Okamoto
6. Seyun Um
7. Xiang Li
8. Guangzhi Sun
9. Jonathan Shen
10. Arijit Mukherjee

Papers from Younggun Lee's perspective

Ordered by how strongly the researchers Younggun Lee 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Voice Imitating Text-to-Speech Neural Networks (2018) — 11 citations
• Robust and Fine-grained Prosody Control of End-to-end Speech Synthesis (2018) — 156 citations
• Emotional End-to-End Neural Speech Synthesizer (2017) — 123 citations