Jaejin Cho
Artificial Intelligence · 2018
A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 41 citations into it; #32,910 of 35,345 by trust here, #20,377 by citations
- Signal Processing — 22 citations into it; #7,498 of 7,572 by trust here, #4,900 by citations
- Speech & Audio — 22 citations into it; #993 of 1,076 by trust here, #752 by citations
- Natural Language Processing — 20 citations into it; #5,611 of 5,688 by trust here, #4,601 by citations
- Model Architectures — 17 citations into it
- Computer Vision and Pattern Recognition — 9 citations into it
Whom Jaejin Cho trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Graves
- Yoshua Bengio
- Dzmitry Bahdanau
- Geoffrey E. Hinton
- Sepp Hochreiter
- Ilya Sutskever
- Karen Simonyan
- Kyunghyun Cho
- J. Urgen Schmidhuber
- Oriol Vinyals
Who trusts Jaejin Cho overall
- Jinyu Li
- Alexis Conneau
- Murali Karthick Baskar
- Shinji Watanabe
- Vineel Pratap
- Alexei Baevski
- Matthew Wiesner
- Kurniawati Azizah
- Oliver Adams
Papers from Jaejin Cho's perspective
Ordered by how strongly the researchers Jaejin Cho 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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)