Bin Wang

Artificial Intelligence · 2 papers · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Signal Processing — 18 citations into it
• Generative Models — 10 citations into it
• Speech & Audio — 9 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Natural Language Processing — 6 citations into it

Whom Bin Wang trusts overall

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

1. Wei Ping
2. Alexia Jolicoeur-Martineau
3. Aäron van den Oord
4. Jean-Marc Valin
5. Wei-Chung Chu
6. Diederik P. Kingma

Papers from Bin Wang's perspective

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

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

Their papers

• Improve GAN-based Neural Vocoder using Pointwise Relativistic LeastSquare GAN (2021)
• The TianQin project: Current progress on science and technology (2020) — 356 citations