Seunghyun Park
Artificial Intelligence · with Lee · 2016–2021
A researcher in the Science corpus: 6 papers; trusts 277 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 130 citations into it; #22,314 of 35,345 by trust here, #16,471 by citations
- Computer Vision and Pattern Recognition — 89 citations into it
- Representation & Self-Supervised Learning — 44 citations into it
- Optimization & Training — 24 citations into it
- Natural Language Processing — 23 citations into it; #3,750 of 5,688 by trust here, #4,112 by citations
- Cancer Research — 18 citations into it; #941 of 1,780 by trust here, #1,628 by citations
- Model Architectures — 16 citations into it
- Molecular Biology — 16 citations into it; #11,569 of 17,773 by trust here, #15,850 by citations
Whom Seunghyun Park trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Kaiming He
- Alex Krizhevsky
- Sergey Ioffe
- Yann LeCun
- Ilya Sutskever
- Christian Szegedy
- Jimmy Ba
Who trusts Seunghyun Park overall
- Mufti Mahmud
- Seonwoo Min
- M. S. Kaiser
- Yiheng Liu
- Byunghan Lee
- Yupan Huang
- Amir Hussain
- Travers Ching
- Jindong Wang
- Geewook Kim
Papers from Seunghyun Park's perspective
Ordered by how strongly the researchers Seunghyun Park 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization (2019) — 276 citations
- SWAD: Domain Generalization by Seeking Flat Minima (2021) — 606 citations
- SelfReg: Self-supervised Contrastive Regularization for Domain Generalization (2021) — 349 citations
- deepMiRGene: Deep Neural Network based Precursor microRNA Prediction (2016) — 50 citations
- CORD: A Consolidated Receipt Dataset for Post-OCR Parsing (2019) — 336 citations
- deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks (2016)