Generative Adversarial Nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley,
Sherjil Ozair†, Aaron Courville, Yoshua Bengio‡
Département d’informatique et de recherche opérationnelle
Université de Montréal
M…The promise of deep learning is to discover rich, hierarchical models [2] that represent probability distributions over the kinds of data encountered in artificial intelligence applications, such as natural images, audio waveforms containin…
Sherjil Ozair
scientist · 2 mentions across 1 reading
In this course
Ozair is a co-author of the foundational "Generative Adversarial Nets" paper, one of the core architectural innovations enabling modern synthetic media generation. His contribution to GANs positions him as part of the team that formalized the adversarial training framework—where a generator and discriminator network compete—which became essential to understanding how machines learn to produce novel outputs rather than merely classify or compress them. Within the course's focus on AI systems that generate culture and intervene in society, GANs represent a critical inflection point where machine learning crosses into creative production and raises questions about authenticity, control, and aesthetic autonomy.
Mentioned in 1 reading
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