Heeyoul Choi
Artificial Intelligence · 2015–2020
A researcher in the Science corpus: 4 papers; trusts 151 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 59 citations into it; #10,393 of 35,345 by trust here, #11,490 by citations
- Natural Language Processing — 52 citations into it; #4,407 of 5,688 by trust here, #3,235 by citations
- Computer Vision and Pattern Recognition — 22 citations into it; #14,925 of 21,575 by trust here, #19,766 by citations
- Model Architectures — 20 citations into it
- Economics and Econometrics — 12 citations into it
- Signal Processing — 11 citations into it; #2,958 of 7,572 by trust here, #4,373 by citations
- Large Language Models — 10 citations into it; #535 of 799 by trust here, #576 by citations
- Optimization & Training — 8 citations into it
Whom Heeyoul Choi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Tomas Mikolov
- Alex Graves
- Oriol Vinyals
- Alex Krizhevsky
- J. Urgen Schmidhuber
- Diederik P. Kingma
- Sepp Hochreiter
Who trusts Heeyoul Choi overall
- Mirco Ravanelli
- Yarin Gal
- Dmitriy Serdyuk
- Shimi Salant
- Jianping Gou
- Sangchul Hahn
- Yoshua Bengio
- Liangchen Luo
- Stanislau Semeniuta
- Qi Liu
Papers from Heeyoul Choi's perspective
Ordered by how strongly the researchers Heeyoul Choi trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- 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
- ImageNet: A large-scale hierarchical image database
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A Neural Knowledge Language Model (2016) — 124 citations
- RNNDROP: A novel dropout for RNNS in ASR (2015) — 114 citations
- Self-Knowledge Distillation in Natural Language Processing (2019) — 135 citations
- A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA (2020) — 147 citations