Applications of physics-informed neural networks in power systems-a review
The advances of deep learning (DL) techniques bring new opportunities to numerous
intractable tasks in power systems (PSs). Nevertheless, the extension of the application of …
intractable tasks in power systems (PSs). Nevertheless, the extension of the application of …
[HTML][HTML] A systematic review of artificial intelligence-based music generation: Scope, applications, and future trends
Currently available reviews in the area of artificial intelligence-based music generation do
not provide a wide range of publications and are usually centered around comparing very …
not provide a wide range of publications and are usually centered around comparing very …
Pop music transformer: Beat-based modeling and generation of expressive pop piano compositions
A great number of deep learning based models have been recently proposed for automatic
music composition. Among these models, the Transformer stands out as a prominent …
music composition. Among these models, the Transformer stands out as a prominent …
A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions
S Ji, J Luo, X Yang - arXiv preprint arXiv:2011.06801, 2020 - arxiv.org
The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
GAN computers generate arts? A survey on visual arts, music, and literary text generation using generative adversarial network
S Shahriar - Displays, 2022 - Elsevier
Abstract “Art is the lie that enables us to realize the truth.”–Pablo Picasso. For centuries,
humans have dedicated themselves to producing arts to convey their imagination. The …
humans have dedicated themselves to producing arts to convey their imagination. The …
AI song contest: Human-AI co-creation in songwriting
Machine learning is challenging the way we make music. Although research in deep
generative models has dramatically improved the capability and fluency of music models …
generative models has dramatically improved the capability and fluency of music models …
Jen-1: Text-guided universal music generation with omnidirectional diffusion models
Music generation has attracted growing interest with the advancement of deep generative
models. However, generating music conditioned on textual descriptions, known as text-to …
models. However, generating music conditioned on textual descriptions, known as text-to …
Learning adversarial transformer for symbolic music generation
N Zhang - IEEE transactions on neural networks and learning …, 2020 - ieeexplore.ieee.org
Symbolic music generation is still an unsettled problem facing several challenges. The
complete music score is a quite long note sequence, which consists of multiple tracks with …
complete music score is a quite long note sequence, which consists of multiple tracks with …
Songmass: Automatic song writing with pre-training and alignment constraint
Automatic song writing aims to compose a song (lyric and/or melody) by machine, which is
an interesting topic in both academia and industry. In automatic song writing, lyric-to-melody …
an interesting topic in both academia and industry. In automatic song writing, lyric-to-melody …
GANmapper: geographical data translation
AN Wu, F Biljecki - International Journal of Geographical …, 2022 - Taylor & Francis
We present a new method to create spatial data using a generative adversarial network
(GAN). Our contribution uses coarse and widely available geospatial data to create maps of …
(GAN). Our contribution uses coarse and widely available geospatial data to create maps of …