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M. Buongiorno Nardelli, "MUSICNTWRK: data tools for music theory, analysis and composition," https://arxiv.org/abs/1906.01453, Springer Lecture Notes in Computer Science,  ''Proceedings of CMMR 2019'', October 14,19, 2019, Marseille, France, in press.
M. Buongiorno Nardelli, "MUSICNTWRK: data tools for music theory, analysis and composition," https://arxiv.org/abs/1906.01453, Springer Lecture Notes in Computer Science,  ''Proceedings of CMMR 2019'', October 14,19, 2019, Marseille, France, in press.
Setzler, M.*, Marghetis, T.*, & Kim, M. (July 2018). Creative leaps in musical ecosystems: Early warning signals of critical transitions in professional jazz. 40th Annual Meeting of the Cognitive Science Society. *joint first authors, https://cogsci.mindmodeling.org/2018/papers/0470/0470.pdf

Revision as of 21:29, 16 November 2020

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Complexity and the Structure of Music: Universal Features and Evolutionary Perspectives Across Cultures
December 7 - 9, 2020 — Zoom

www.materialssoundmusic.com

www.musicntwrk.com

M. Buongiorno Nardelli, "The hitchhiker’s guide to the all-interval 12-tone rows," submitted (2020), also at https://arxiv.org/abs/2006.05007

M. Buongiorno Nardelli, "Tonal harmony, the topology of dynamical score networks and the Chinese postman problem," submitted (2020), also at https://arxiv.org/abs/2006.01033

M. Buongiorno Nardelli, "Topology of Networks in Generalized Musical Spaces," Leonardo Music Journal, Accepted at https://www.mitpressjournals.org/doi/abs/10.1162/lmj_a_01079 (2020), also at https://arxiv.org/pdf/1905.01842.pdf

M. Buongiorno Nardelli, "MUSICNTWRK: data tools for music theory, analysis and composition," https://arxiv.org/abs/1906.01453, Springer Lecture Notes in Computer Science, Proceedings of CMMR 2019, October 14,19, 2019, Marseille, France, in press.

Setzler, M.*, Marghetis, T.*, & Kim, M. (July 2018). Creative leaps in musical ecosystems: Early warning signals of critical transitions in professional jazz. 40th Annual Meeting of the Cognitive Science Society. *joint first authors, https://cogsci.mindmodeling.org/2018/papers/0470/0470.pdf