Minbyul Jeong
Artificial Intelligence · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 50 citations into it
- Graph Learning — 27 citations into it
- Natural Language Processing — 22 citations into it
- Statistical and Nonlinear Physics — 13 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Molecular Biology — 7 citations into it
- Evaluation & Benchmarks — 5 citations into it
Whom Minbyul Jeong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thomas Kipf
- Geoffrey E. Hinton
- Diederik P. Kingma
- Max Welling
- Yoshua Bengio
- Yann LeCun
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Alex Graves
Who trusts Minbyul Jeong overall
Papers from Minbyul Jeong's perspective
Ordered by how strongly the researchers Minbyul Jeong 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Graph Transformer Networks (2019) — 1,382 citations
- Learning by Semantic Similarity Makes Abstractive Summarization Better (2020) — 18 citations