1.1 - Oversight of current sources

This first part of my sources is here to remind me of what I'm doing and are trying to do in comparison to other projects. It contains some interesting works on which I will be grounding my further development of my own neuralmusic. Or actually just computer generated music.
[1] Li-Chia Yang, Szu-Yu Chou, and Yi-Hsuan Yang. Midinet: A convolutional generative adversarial network for symbolic-domain music generation using 1d and 2d conditions. arXiv preprint arXiv:1703.10847, 2017. [ bib ]
[2] Gabriel Sargent, Frédéric Bimbot, and Emmanuel Vincent. Estimating the structural segmentation of popular music pieces under regularity constraints. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25(2):344--358, 2017. [ bib ]
[3] Pieter Adriaans, Henning Fernau, and Menno van Zaanen. Grammatical Inference: Algorithms and Applications: 6th International Colloquium: ICGI 2002, Amsterdam, The Netherlands, September 23-25, 2002. Proceedings, volume 2484. Springer Science & Business Media, 2002. [ bib ]
[4] Ian Goodfellow. Nips 2016 tutorial: Generative adversarial networks. arXiv preprint arXiv:1701.00160, 2016. [ bib ]
[5] James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. Overcoming catastrophic forgetting in neural networks. Proceedings of the National Academy of Sciences, page 201611835, 2017. [ bib ]
[6] Nima Mesgarani, Connie Cheung, Keith Johnson, and Edward F Chang. Phonetic feature encoding in human superior temporal gyrus. Science, 343(6174):1006--1010, 2014. [ bib ]
[7] Dana L Strait and Nina Kraus. Biological impact of auditory expertise across the life span: musicians as a model of auditory learning. Hearing research, 308:109--121, 2014. [ bib ]
[8] Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning. MIT Press, 2016. http://www.deeplearningbook.org. [ bib ]
This file was generated by bibtex2html 1.98.

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