Byunghan Lee

Artificial Intelligence · 2016

A researcher in the Science corpus: 2 papers; trusts 273 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it
• Computer Vision and Pattern Recognition — 54 citations into it
• Molecular Biology — 37 citations into it; #8,574 of 17,773 by trust here, #7,384 by citations
• Model Architectures — 32 citations into it
• Optimization & Training — 29 citations into it
• Natural Language Processing — 19 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Cancer Research — 12 citations into it

Whom Byunghan Lee trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Alex Graves
5. Yann LeCun
6. Alex Krizhevsky
7. Ilya Sutskever
8. J. Urgen Schmidhuber
9. Ruslan Salakhutdinov
10. Kyunghyun Cho

Who trusts Byunghan Lee overall

1. Mufti Mahmud
2. Seonwoo Min
3. Luigi Troiano
4. A. Navon
5. M. S. Kaiser
6. Ehsaneddin Asgari
7. Alexandru Korotcov
8. Elena Mejuto Villa
9. Travers Ching
10. Sungroh Yoon

Papers from Byunghan Lee's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Deep learning in bioinformatics (2016) — 1,486 citations
• deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks (2016)