Method evidence record
Generative Adversarial Network
A Generative Adversarial Network (GAN), introduced by Ian Goodfellow and colleagues in 2014, produces realistic synthetic data through the competition of two neural networks — a generator and a discriminator. It is widely used for image synthesis, data augmentation, and distribution estimation.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Generative Adversarial Network (GAN)
Taxonomic method record · ml-model / deep-learning
- Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS. · URL
- Karras, T. et al. (2020). Analyzing and Improving the Image Quality of StyleGAN. CVPR. · DOI 10.1109/CVPR42600.2020.00813
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.