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Magenta (music and art generation with machine intelligence)

Magenta (music and art generation with machine intelligence)

A research project devoted to develop deep learning and reinforcement learning algorithms for creating art and music

Magenta is a research project analyzing the function of machine learning in creating art and music.

Magenta focuses on developing new deep learning and reinforcement learning algorithms for generating songs, images, drawings and other materials. It also constructs smart tools and interfaces allowing artists and musicians to extend their processes using these models.

The started in 2016 by researchers and engineers from the Google Brain team. It is led by Doug Eck, a research scientist. They use TensorFlow and release their models and tools in open source on GitHub.

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Further reading

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Aaron van den Oord, Nal Kalchbrenner and Koray Kavukcuoglu

Pixel Recurrent Neural Networks

Academic paper

Alex Graves

Generating Sequences With Recurrent Neural Networks

Academic paper

Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende and Daan Wierstra

DRAW: A Recurrent Neural Network For Image Generation

Academic paper

Leon A. Gatys, Alexander S. Ecker and Matthias Bethge

A Neural Algorithm of Artistic Style

Academic paper

Nicolas Boulange, Yoshua Bengio and Pascal Vincent

Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription

Academic paper

Documentaries, videos and podcasts

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Magenta: Music and Art Generation (TensorFlow Dev Summit 2017)

15 February 2017

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