Gyeongsu Chae

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it
• Generative Models — 24 citations into it
• Signal Processing — 24 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Speech & Audio — 14 citations into it

Whom Gyeongsu Chae trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton

Papers from Gyeongsu Chae's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Attention is All you Need (Neural Information Processing Systems)
3. GENERATIVE ADVERSARIAL NETS
4. ImageNet classification with deep convolutional neural networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. WaveNet: A Generative Model for Raw Audio
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• GAN Vocoder: Multi-Resolution Discriminator Is All You Need (2021) — 33 citations
• Axial Residual Networks for CycleGAN-based Voice Conversion (2021) — 3 citations