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Machine learning models of music typically break up the task of composition into a chronological process, composing a piece of music in a single pass from beginning to end.
Musical composition with a high speed digital computer
Lejaren A Hiller Jr and Leonard M Isaacson · 1957
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The study of counterpoint from Johann Joseph Fux’s Gradus ad Parnassum
Johann Joseph Fux · 1965
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Statistical inference for probabilistic functions of finite state markov chains
Leonard E Baum and Ted Petrie · 1966
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Information processing in dynamical systems: Foundations of harmony theory
Paul Smolensky · 1986
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Nonuniversal critical dynamics in monte carlo simulations
Robert H Swendsen and Jian-Sheng Wang · 1987
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Learning representations by back-propagating errors
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams · 1988
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Computers and musical style
David Cope · 1991
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The collapsed gibbs sampler in bayesian computations with applications to a gene regulation problem
Jun S Liu · 1994
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Analysis and synthesis of palestrina-style counterpoint using markov chains
Mary Farbood and Bernd Schöner · 2001
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Musical harmonization with constraints: A survey
François Pachet and Pierre Roy · 2001
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Music generation from statistical models
Darrell Conklin · 2003
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Harmonising chorales by probabilistic inference
Moray Allan and Christopher KI Williams · 2005
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Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh · 2006
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Hugo Larochelle and Iain Murray · 2011
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Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription
Nicolas Boulanger-Lewandowski, Yoshua Bengio, and Pascal Vincent · 2012
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Dorien Herremans and Kenneth Sörensen · 2013
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