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Generating music with deep neural networks has been an area of active research in recent years.
Real-time chord recognition of musical sound: A system using common lisp music
Takuya Fujishima · 1999
Earlier work this paper cites.
Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions
Yu-Siang Huang and Yi-Hsuan Yang · 2002
Earlier work this paper cites.
Towards Characterisation of Music via Rhythmic Patterns
Simon Dixon, Fabien Gouyon, and Gerhard Widmer · 2004
Earlier work this paper cites.
Jukebox: A Generative Model for Music
Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, and Ilya Sutskever · 2005
Earlier work this paper cites.
Hao Hao Tan and Dorien Herremans · 2007
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MMM : Exploring Conditional Multi-Track Music Generation with the Transformer
Jeff Ens and Philippe Pasquier · 2008
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Improve Transformer Models with Better Relative Position Embeddings
Zhiheng Huang, Davis Liang, Peng Xu, and Bing Xiang · 2009
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Historical Development of Algorithmic Procedures
Gerhard Nierhaus · 2009
Earlier work this paper cites.
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2010
Earlier work this paper cites.
Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching
Colin Raffel · 2016
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba · 2017
Earlier work this paper cites.
Attention is All you Need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer
Gino Brunner, Andres Konrad, Yuyi Wang, and Roger Wattenhofer · 2018
Cited alongside, same era.
Avoiding latent variable collapse with generative skip models, 2018
Adji B. Dieng, Yoon Kim, Alexander M. Rush, and David M. Blei · 2018
Cited alongside, same era.
Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Ian Simon, Curtis Hawthorne, Andrew M. Dai, Matthew D. Hoffman, Monica Dinculescu, and Douglas Eck · 2018
Cited alongside, same era.
Fast Decoding in Sequence Models using Discrete Latent Variables
Encoding Musical Style with Transformer Autoencoders
Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, and Jesse Engel · 2020
Later among the works it cites.
Neural symbolic regression that scales
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, and Giambattista Parascandolo · 2021
Later among the works it cites.
Video Background Music Generation with Controllable Music Transformer
Shangzhe Di, Zeren Jiang, Si Liu, Zhaokai Wang, Leyan Zhu, Zexin He, Hongming Liu, and Shuicheng Yan · 2021
Later among the works it cites.
Learning to Generate Music With Sentiment
Lucas N. Ferreira and Jim Whitehead · 2021
Later among the works it cites.
Music Composition with Deep Learning: A Review
Carlos Hernandez-Olivan and Jose R. Beltran · 2021
Later among the works it cites.
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Łukasz Kaiser, Aurko Roy, Ashish Vaswani, Niki Parmar, Samy Bengio, Jakob Uszkoreit, and Noam Shazeer · 2018
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Neural Discrete Representation Learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2018
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Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2019
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MuseNet, April 2019
Christine Payne · 2019
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Language models are few-shot learners, 2020
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Cited alongside, same era.
Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, and Yi-Hsuan Yang · 2021
Later among the works it cites.
MuseMorphose: Full-Song and Fine-Grained Music Style Transfer with Just One Transformer VAE
Shih-Lun Wu and Yi-Hsuan Yang · 2021
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Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Photorealistic text-to-image diffusion models with deep language understanding, 2022
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