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Recurrent Neural Networks (RNNS) are now widely used on sequence generation tasks due to their ability to learn long-range dependencies and to generate sequences of arbitrary length.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Methods of information geometry
S.-i. Amari and H. Nagaoka · 2007
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music21: A toolkit for computer-aided musicology and symbolic music data
M. S. Cuthbert and C. Ariza · 2010
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The Burbea-Rao and Bhattacharyya centroids
F. Nielsen and S. Boltz · 2011
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Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription
N. Boulanger-lewandowski, Y. Bengio, and P. Vincent · 2012
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Imitative leadsheet generation with user constraints
F. Pachet and P. Roy · 2014
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https://github.com/pytorch/pytorch , 2016
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Music transcription modelling and composition using deep learning, Apr. 2016
B. L. Sturm, J. F. Santos, O. Ben-Tal, and I. Korshunova · 2016
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Deep artificial composer: A creative neural network model for automated melody generation
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Automated curriculum learning for neural networks
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DeepBach: a steerable model for Bach chorales generation
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Maximum entropy models capture melodic styles
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