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  1. en.wikipedia.org › wiki › Ian_GoodfellowIan Goodfellow - Wikipedia

    Ian J. Goodfellow (born 1987) is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning.

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    • How Ian Goodfellow Invented GANs
    • Consomac : Intelligence artificielle : Ian Goodfellow rejoint Apple
    • Ian Goodfellow 谈 GANs 论文评审：有这些迹象的论文要怀疑

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  3. scholar.google.com.sg › citations‪Ian Goodfellow‬ - ‪Google Scholar‬

    Ian Goodfellow. DeepMind. Verified email at deepmind.com - Homepage. Deep Learning. Articles 1–20. ‪DeepMind‬ - ‪‪Cited by 292,603‬‬ - ‪Deep Learning‬.

  4. de.wikipedia.org › wiki › Ian_GoodfellowIan Goodfellow – Wikipedia

    Ian Goodfellow. Ian Goodfellow (geboren 1987) ist ein amerikanischer Informatiker und ehemaliger Director of Machine Learning bei Apple Inc. Leben und Wirken. Ian Goodfellow studierte an der Stanford University und promovierte anschließend an der Université de Montréal.

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  6. www.linkedin.com › in › ian-goodfellow-b7187213Ian Goodfellow - DeepMind | LinkedIn

    Ian Goodfellow is an industry leader in machine learning and a researcher at DeepMind. He invented generative adversarial networks and other techniques, and won the National Academy of Sciences award in 2022.

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    • Deepmind
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    • San Francisco Bay Area

  7. www.deeplearningbook.orgDeep Learning

    Deep Learning. An MIT Press book. Ian Goodfellow and Yoshua Bengio and Aaron Courville. Exercises &nbsp Lectures &nbsp External Links &nbsp. The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.

  8. www.iangoodfellow.com › bioBio - Ian Goodfellow

    Ian Goodfellow is a leading expert in deep learning, machine learning security and privacy. He developed the first defenses against adversarial examples, wrote a popular textbook on deep learning, and worked at OpenAI and Willow Garage.

  9. arxiv.org › abs › 1406[1406.2661] Generative Adversarial Networks - arXiv.org

    10. Juni 2014 · Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. We propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a ...