Creativity in Machine Learning

Preprint English OPEN
Thoma, Martin;
  • Subject: Computer Science - Computer Vision and Pattern Recognition | Computer Science - Learning

Recent machine learning techniques can be modified to produce creative results. Those results did not exist before; it is not a trivial combination of the data which was fed into the machine learning system. The obtained results come in multiple forms: As images, as tex... View more
  • References (18)
    18 references, page 1 of 2

    --, “Composing music with recurrent neural networks,” Personal Blog, Aug. 2015. [Online]. Available: composing-music-with-recurrent-neural-networks/

    J. Johnson, “neural-style,” GitHub, Jan. 2016. [Online]. Available:

    A. Karpathy, “char-rnn,” GitHub, Nov. 2015. [Online]. Available:

    --, “The unreasonable effectiveness of recurrent neural networks,” Personal Blog, May 2015. [Online]. Available:

    T. M. Mitchell, Machine learning, ser. McGraw Hill series in computer science. McGraw-Hill, 1997.

    A. Mordvintsev, C. Olah, and M. Tyka, “Inceptionism: Going deeper into neural networks,”, Jun. 2015. [Online]. Available: 2015/06/inceptionism-going-deeper-into-neural.html

    M. A. Nielsen, Neural Networks and Deep Learning. Determination Press, 2015. [Online]. Available: introducing convolutional networks

    A. Nayebi and M. Vitelli, “GRUV: Algorithmic music generation using recurrent neural networks,” 2015. [Online]. Available:

    2014. [Online]. Available: Hj5lGFzlubU

    Y. Shih, S. Paris, C. Barnes, W. T. Freeman, and F. Durand, “Style transfer for headshot portraits,” ACM Transactions on Graphics (TOG), vol. 33, no. 4, p. 148, 2014. [Online]. Available:

  • Related Research Results (3)
  • Metrics
Share - Bookmark