Papers

• Jean-Pierre Briot, From artificial neural networks to deep learning for music generation - History, concepts and trends, Neural Computing and Applications (NCAA), Special issue Networks in art, sound and design, October 2020. ISSN (Print): 0941-0643. ISSN (Online): 1433-3058. DOI: 10.1007/s00521-020-05399-0. Web. ArXiV Version: Web.

• Jean-Pierre Briot, Compress to Create, MusMat: Brazilian Journal of Music and Mathematics, IV(1):12--38, June 2020. ISSN: 2526-3757. Invited article. Web. HAL preprint Web. MIDI files of the examples

• Jean-Pierre Briot and François Pachet, Music generation by deep learning - Challenges and directions. Neural Computing and Applications (NCAA). Special Issue Deep learning for music and audio, 32(4):981-993, January 2020. ISSN (Print): 0941-0643. ISSN (Online): 1433-3058. DOI: 10.1007/s00521-018-3813-6. Web. ArXiV Version: Web

• Jean-Pierre Briot, Gaëtan Hadjeres and François-David Pachet, Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems Series, Springer Verlag, 2019. ISBN: 978-3-319-70162-2. DOI: https://doi.org/10.1007/978-3-319-70163-9_1 Web. Companion Mini Web Site.

• Jean-Pierre Briot, Apprentissage profond et génération de musique, Hors série Intelligence artificielle, Tangente - L'aventure mathématique, (68):30-37, September 2019. ISSN: 0987-0806. PDF.

• Jean-Pierre Briot, Gaëtan Hadjeres and François Pachet, Deep Learning Techniques for Music Generation - A Survey, arXiv:1709.01620, September 2017, November 2018, March 2019, August 2019. Web

Some recent Webinar on the topic (in french - slides in english) at Forum Numerica, Sophia-Antipolis, 25/06/2020.

Jean-Pierre.Briot, 23/10/2020.