Youngjun Kwak

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 45 citations into it
• Artificial Intelligence — 39 citations into it
• Efficiency & Compression — 24 citations into it
• Model Architectures — 7 citations into it

Whom Youngjun Kwak trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ross B. Girshick
6. X. Zhang
7. Shaoqing Ren
8. Ilya Sutskever
9. Karen Simonyan
10. Yann LeCun

Papers from Youngjun Kwak's perspective

Ordered by how strongly the researchers Youngjun Kwak 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. Learning Multiple Layers of Features from Tiny Images
4. ImageNet Large Scale Visual Recognition Challenge
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss (2018) — 430 citations
• Joint Training of Low-Precision Neural Network with Quantization Interval Parameters (2018) — 36 citations