(Re)discovering Laws of Music Theory Using Information Lattice Learning-Reference-Cited by-同舟云学术

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(Re)discovering Laws of Music Theory Using Information Lattice Learning

Published:2022 Issue: Volume: Page:1-13
ISSN:2692-4110
Container-title:IEEE BITS the Information Theory Magazine
language:
Short-container-title:IEEE BITS Inform. Theory Mag.

Author:

Yu Haizi¹,Varshney Lav R.²^ORCID,Taube Heinrich³,Evans James A.⁴

Affiliation:

1. Knowledge Lab, University of Chicago, Chicago, IL, USA

2. Coordinated Science Laboratory and the Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA

3. School of Music, University of Illinois Urbana-Champaign, Urbana, IL, USA

4. Department of Sociology, University of Chicago, Chicago, IL, USA

Funder

NSF

IBM-Illinois Center for Cognitive Computing Systems Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9393008/9507336/09882090.pdf?arnumber=9882090

Reference46 articles.

1. Innateness, AlphaZero, and artificial intelligence;marcus,2018

2. Universal Compression of Memoryless Sources Over Unknown Alphabets

3. Limits theorems for creativity with intentionality;varshney;Proc 11th Int Conf Comput Creativity,0

4. Music transformer;huang,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Semantic Compression with Information Lattice Learning;2024 IEEE International Symposium on Information Theory Workshops (ISIT-W);2024-07-07

2. Suno: potential, prospects, and trends;Frontiers of Information Technology & Electronic Engineering;2024-06-20

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