2014 CE
Generative adversarial networks
Artificial intelligence · Machine learning
Ian Goodfellow and colleagues introduce GANs, a learning framework that advances synthetic generation of images and other data. Training pits a generator against a discriminator; sample quality does not guarantee factual accuracy.
Precision, calendar, and review
- Start
- year · no uncertainty qualifier in this record
- Calendar and convention
- Historical-era years; the source calendar is not identified. No conversion of days is assumed.
- Year zero
- The scale goes from 1 BCE to 1 CE without year zero. Changing era names changes labels only.
- Documentary review
- 2026-09-20
Reading the date: point event.
Sources
- arxiv.org (opens in a new tab)
Source provenance and scope
- Publication date
- 2014-06-10
- What this date describes
- The cited source or edition; it may postdate the historical event.
- Date note
- Date of the first arXiv preprint version; later revisions may exist.
- Bibliographic date checked
- 2026-09-23
- Date evidence
- Declared in the cited source’s publisher metadata.
- Access date
- 2026-09-20
The correspondence between this reference and individual claims has not yet been itemized.
This record is an editorial synthesis. Consult the sources to check claims and their limits. Chronological relationships alone do not establish causation.