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  2. Ian Goodfellow - Wikipedia

    en.wikipedia.org/wiki/Ian_Goodfellow

    Ian J. Goodfellow (born 1987 [1]) is an American computer scientist, engineer, and executive, most noted for his work on artificial neural networks and deep learning.He is a research scientist at Google DeepMind, [2] was previously employed as a research scientist at Google Brain and director of machine learning at Apple as well as one of the first employees at OpenAI, and has made several ...

  3. Apple lures another of Google's top experts to its AI team - AOL

    www.aol.com/news/2019-04-05-apple-google...

    Apple has named Ian Goodfellow as the Director of Machine Learning in the Special Projects Group last month. Apple lures another of Google's top experts to its AI team Skip to main content

  4. Yoshua Bengio - Wikipedia

    en.wikipedia.org/wiki/Yoshua_Bengio

    Yoshua Bengio OC FRS FRSC (born March 5, 1964 [3]) is a Canadian computer scientist, and a pioneer of artificial neural networks and deep learning. [4] [5] [6] He is a professor at the Université de Montréal and scientific director of the AI institute MILA.

  5. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence.The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. [1]

  6. Andrew Ng - Wikipedia

    en.wikipedia.org/wiki/Andrew_Ng

    His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [23] [24] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6). [25]

  7. Mamba (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Mamba_(deep_learning...

    Mamba [a] is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University to address some limitations of transformer models , especially in processing long sequences.