Shou-De Lin

Signal Processing · with Fu · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 20 citations into it
• Artificial Intelligence — 12 citations into it
• Speech & Audio — 12 citations into it
• Computational Mechanics — 6 citations into it

Whom Shou-De Lin trusts overall

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

1. Diederik P. Kingma
2. Mira Lilleholt Vik

Papers from Shou-De Lin's perspective

Ordered by how strongly the researchers Shou-De Lin 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. GENERATIVE ADVERSARIAL NETS
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Image-to-Image Translation with Conditional Adversarial Networks
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Conditional Generative Adversarial Nets
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement (2019) — 419 citations