Soo-Young Lee

Signal Processing · with Lee · 2005–2018

A researcher in the Science corpus: 4 papers; trusts 83 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 32 citations into it; #4,288 of 7,572 by trust here, #3,566 by citations
• Artificial Intelligence — 21 citations into it; #22,751 of 35,345 by trust here, #22,463 by citations
• Speech & Audio — 15 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Natural Language Processing — 13 citations into it
• Computational Mechanics — 9 citations into it; #9,658 of 10,001 by trust here, #7,501 by citations
• Model Architectures — 9 citations into it
• Analytical Chemistry — 8 citations into it

Whom Soo-Young Lee trusts overall

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

1. Andrzej S. Cichocki
2. Shun-ichi Amari
3. Jean-François Cardoso
4. Michael S. Lewicki
5. Wolfram Liebermeister
6. Anthony J. Bell
7. Scott Makeig
8. Terrence J. Sejnowski
9. Antoine Souloumiac
10. Lucas C. Parra

Who trusts Soo-Young Lee overall

1. Yangyang Xu
2. Yi Luo
3. Eliya Nachmani
4. Wotao Yin
5. Yossi Adi
6. Zhuo Chen
7. Nima Mesgarani
8. Lior Wolf
9. Irene Winkler

Papers from Soo-Young Lee's perspective

Ordered by how strongly the researchers Soo-Young Lee trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
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
• Emotional End-to-End Neural Speech Synthesizer (2017) — 123 citations
• Blind Source Separation Exploiting Higher-Order Frequency Dependencies (2007) — 468 citations
• Blind Source Separation and Independent Component Analysis: A Review (2005) — 272 citations