Minseop Park

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 3 papers; trusts 128 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 56 citations into it
• Computer Vision and Pattern Recognition — 51 citations into it
• Representation & Self-Supervised Learning — 41 citations into it
• Optimization & Training — 12 citations into it
• Model Architectures — 9 citations into it
• Reinforcement Learning — 9 citations into it

Whom Minseop Park trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Oriol Vinyals
6. Sergey Ioffe
7. Kaiming He
8. Ilya Sutskever
9. J. Urgen Schmidhuber
10. Ruslan Salakhutdinov

Papers from Minseop Park's perspective

Ordered by how strongly the researchers Minseop Park trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning to Propagate Labels: Transductive Propagation Network for Few-Shot Learning (2018) — 758 citations
• Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks (2019) — 116 citations
• Transductive Propagation Network for Few-shot Learning (2018) — 81 citations