Jinbae Im

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 59 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it; #14,408 of 35,345 by trust here, #25,809 by citations
• Natural Language Processing — 20 citations into it; #2,670 of 5,688 by trust here, #5,092 by citations
• Computer Vision and Pattern Recognition — 18 citations into it
• Information Systems — 12 citations into it
• Representation & Self-Supervised Learning — 11 citations into it
• Model Architectures — 9 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Jinbae Im trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Tsendsuren Munkhdalai
5. Alex Graves
6. Yoshua Bengio
7. Ilya Sutskever
8. Samuel R. Bowman
9. Alex Krizhevsky
10. Sepp Hochreiter

Who trusts Jinbae Im overall

1. Jamie Ryan Kiros
2. Tianyi Zhou
3. Nikhita Vedula
4. William Chan
5. Guodong Long
6. Nedim Lipka
7. Geoffrey E. Hinton
8. Yuanfu Lu
9. Jing Jiang
10. Pranav Maneriker

Papers from Jinbae Im's perspective

Ordered by how strongly the researchers Jinbae Im 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Distance-based Self-Attention Network for Natural Language Inference (2017) — 76 citations
• MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation (2019) — 469 citations