Ping Chen

Computer Vision and Pattern Recognition · with Cui · 2021

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

Subfields

• Computer Vision and Pattern Recognition — 19 citations into it
• Generative Models — 19 citations into it

Whom Ping Chen trusts

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

1. Alexia Jolicoeur-Martineau (in Computer Vision and Pattern Recognition)

Papers from Ping Chen's perspective

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

1. GENERATIVE ADVERSARIAL NETS
2. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
3. Going deeper with convolutions
4. Improved Training of Wasserstein GANs
5. Wasserstein GAN
6. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
7. Towards Principled Methods for Training Generative Adversarial Networks
8. Energy-based Generative Adversarial Network
9. Spectral Normalization for Generative Adversarial Networks
10. Least Squares Generative Adversarial Networks

Their papers

• Hausdorff GAN: Improving GAN Generation Quality With Hausdorff Metric (2021) — 34 citations