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  1. Dalle Molle Institute for Artificial Intelligence Research. Thesis. Supervised sequence labelling with recurrent neural networks (2008) Doctoral advisor. Jürgen Schmidhuber. Website. www .cs .toronto .edu /~graves. Alex Graves is a computer scientist and research scientist at DeepMind. [1]

  2. en.wikipedia.org › wiki › Alex_GravesAlex Graves - Wikipedia

    July 23, 1965 (age 58) Kansas City, Missouri. Occupation (s) Film director, television director, television producer, screenwriter. Alexander John Graves (born July 23, 1965) is an American film director, television director, television producer and screenwriter .

  3. Alex Graves. University of Toronto. Verified email at cs.toronto.edu - Homepage. Artificial Intelligence Recurrent Neural Networks Handwriting Recognition Speech recognition. Title. Sort. Sort by citations Sort by year Sort by title. Cited by.

  4. www.imdb.com › name › nm0336241Alex Graves - IMDb

    Alex Graves is known for The West Wing (1999), Foundation (2021) and Game of Thrones (2011). More at IMDbPro. Contact info. Agent info. Resume. Add to list. Won 2 Primetime Emmys. 3 wins & 19 nominations total. Known for. The West Wing. 8.9. TV Series. Producer. 2001–2006 • 104 eps. Foundation. 7.6. TV Series. Producer. 2023 • 10 eps.

    • Producer, Director, Writer
    • Alex Graves
  5. deepai.org › profile › alex-gravesAlex Graves | DeepAI

    Multi-Dimensional Recurrent Neural Networks. Recurrent neural networks (RNNs) have proved effective at one dimensiona... Alex Graves is a DeepMind research scientist. He received a BSc in Theoretical Physics from Edinburgh and an AI PhD from IDSIA under Jürgen Schmidhuber.

  6. Alex Graves. I'm a CIFAR Junior Fellow supervised by Geoffrey Hinton in the Department of Computer Science at the University of Toronto. email: graves@cs.toronto.edu . Research Interests. Recurrent neural networks (especially LSTM) Supervised sequence labelling (especially speech and handwriting recognition) Unsupervised sequence learning. Demos.

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  8. Aug 4, 2013 · Alex Graves. This paper shows how Long Short-term Memory recurrent neural networks can be used to generate complex sequences with long-range structure, simply by predicting one data point at a time. The approach is demonstrated for text (where the data are discrete) and online handwriting (where the data are real-valued).

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