Youngjune Gwon

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 328 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it; #8,946 of 21,575 by trust here, #7,027 by citations
• Generative Models — 60 citations into it; #850 of 1,956 by trust here, #786 by citations
• Artificial Intelligence — 35 citations into it
• Model Architectures — 11 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Reinforcement Learning — 7 citations into it
• Multimodal Learning — 6 citations into it
• Optimization & Training — 6 citations into it

Whom Youngjune Gwon trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Christian Szegedy
6. Kaiming He
7. Ilya Sutskever
8. Yann LeCun
9. Scott E. Reed
10. Jimmy Ba

Who trusts Youngjune Gwon overall

1. Hyungjin Chung
2. Tobias Hinz
3. Chao Zhang
4. Stanislav Frolov
5. Jong Chul Ye
6. Hui Ye

Papers from Youngjune Gwon's perspective

Ordered by how strongly the researchers Youngjune Gwon 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models (2021) — 969 citations
• Adversarial Learning of Semantic Relevance in Text to Image Synthesis (2018) — 60 citations
• POMO: Policy Optimization with Multiple Optima for Reinforcement Learning (2020) — 645 citations