Yuxuan Song

Generative Models · with Yu · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 26 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Generative Models — 48 citations into it
• Computer Vision and Pattern Recognition — 46 citations into it
• Artificial Intelligence — 22 citations into it
• Statistical and Nonlinear Physics — 7 citations into it

Whom Yuxuan Song trusts overall

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

1. Individualized Treat
2. Sebastian Nowozin
3. Yoshua Bengio
4. Ian J. Goodfellow
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Yann LeCun
9. Xudong Mao
10. Jinsung Yoon

Who trusts Yuxuan Song overall

1. Ting-Li Chen

Papers from Yuxuan Song's perspective

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

Their papers

• Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis (2018) — 7 citations
• Activation Maximization Generative Adversarial Nets (2017) — 80 citations