Philippe Esling, Axel Chemla-Romeu-Santos, and Adrien Bitton. Bridging audio analysis, perception and synthesis with perceptually-regularized variational timbre spaces. In Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018, pages 175–181, 2018.
Eric Foxley. Nottingham database, 2011.
Beat Gfeller, Christian Frank, Dominik Roblek, Matt Sharifi, Marco Tagliasacchi, and Mihajlo Velimirovic. Spice: Self-supervised pitch estimation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28:1118-1128, 2020.
Irina Higgins, David Amos, David Pfau, Sebastien Racaniere, Loic Matthew, Danilo Rezende, and Alexander Lerchner. Towards a definition of disentangled representations. arXiv preprint arXiv:1812.02230, 2018.
Wei-Ning Hsu, Yu Zhang, and James Glass. Unsupervised learning of disentangled and interpretable representations from sequential data. Advances in Neural Information Processing Systems, 30, 2017.
Siyuan Huang, Yichen Xie, Song-Chun Zhu, and Yixin Zhu. Spatio-temporal self-supervised representation learning for 3d point clouds. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 6535-6545, 2021.
Dasaem Jeong, Taegyun Kwon, Yoojin Kim, and Juhan Nam. Graph neural network for music score data and modeling expressive piano performance. In International Conference on Machine Learning, pages 3060-3070. PMLR, 2019.
Shulei Ji, Jing Luo, and Xinyu Yang. A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions. arXiv preprint arXiv:2011.06801, 2020.
David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, and Dylan Paiton. Towards nonlinear disentanglement in natural data with temporal sparse coding. In International Conference on Learning Representations, 2021.
Yann LeCun. A path towards autonomous machine intelligence. preprint posted on openreview, 2022.
Liwei Lin, Gus Xia, Qiuqiang Kong, and Junyan Jiang. A unified model for zero-shot music source separation, transcription and synthesis. In Jin Ha Lee, Alexander Lerch, Zhiyao Duan, Juhan Nam, Preeti Rao, Peter van Kranenburg, and Ajay Srinivasamurthy, editors, Proceedings of the 22nd International Society for Music Information Retrieval Conference, ISMIR 2021, pages 381-388, 2021.
Yin-Jyun Luo, Kat Agres, and Dorien Herremans. Learning disentangled representations of timbre and pitch for musical instrument sounds using gaussian mixture variational autoencoders. Proceedings of the 20th International Society for Music Information Retrieval Conference, ISMIR 2019, 2019.
Yin-Jyun Luo, Kin Wai Cheuk, Tomoyasu Nakano, Masataka Goto, and Dorien Herremans. Unsupervised disentanglement of pitch and timbre for isolated musical instrument sounds. In Proceedings of the 21st International Society for Music Information Retrieval Conference, ISMIR 2020, pages 700-707, 2020.
Yin-Jyun Luo, Sebastian Ewert, and Simon Dixon. Towards robust unsupervised disentanglement of sequential data — a case study using music audio. In Lud De Raedt, editor, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pages 3299–3305. International Joint Conferences on Artificial Intelligence Organization, 7 2022. Main Track.
Ollie McCarthy and Zohaib Ahmed. Hooligan: Robust, high quality neural vocoding. arXiv preprint arXiv:2008.02493, 2020.
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger. Occupancy networks: Learning 3d reconstruction in function space. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 4460-4470, 2019.