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.
A Neural Algorithm of Artistic Style
Leon A. Gatys, Alexander S. Ecker and Matthias Bethge
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende and Daan Wierstra
Generating Sequences With Recurrent Neural Networks
Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription
Nicolas Boulange, Yoshua Bengio and Pascal Vincent
Pixel Recurrent Neural Networks
Aaron van den Oord, Nal Kalchbrenner and Koray Kavukcuoglu
Documentaries, videos and podcasts
Magenta: Music and Art Generation (TensorFlow Dev Summit 2017)
15 February 2017
- Machine learningA field of computer science enabling computers to learn.
- Deep learningBranch of machine learning based on learning data representations.
- Reinforcement LearningAn area of machine learning focusing on how machines and software agents react in a specific context to maximize performance and achieve reward known as reinforcement signal.