22 citations · 24 across the 6 of their papers we have counts for
7 papers
Identifying the nonlinear string dynamics with port-Hamiltonian neural networks
Maximino Linares, Guillaume Doras, Thomas Hélie
Hybrid machine learning combines physical knowledge with data-driven models to enhance interpretability and performance. In this context, Port-Hamiltonian Systems (PHS), which gene…
Controlled oscillation modeling using port-Hamiltonian neural networks
Maximino Linares, Guillaume Doras, Thomas Hélie
Learning dynamical systems through purely data-driven methods is challenging as they do not learn the underlying conservation laws that enable them to correctly generalize. Existin…
Combining audio control and style transfer using latent diffusion
Nils Demerlé, Philippe Esling, Guillaume Doras +1
Deep generative models are now able to synthesize high-quality audio signals, shifting the critical aspect in their development from audio quality to control capabilities. Although…
And what if two musical versions don't share melody, harmony, rhythm, or lyrics ?
Mathilde Abrassart, Guillaume Doras
Version identification (VI) has seen substantial progress over the past few years. On the one hand, the introduction of the metric learning paradigm has favored the emergence of sc…
Audio-based Musical Version Identification: Elements and Challenges
Furkan Yesiler, Guillaume Doras, Rachel M. Bittner +2
In this article, we aim to provide a review of the key ideas and approaches proposed in 20 years of scientific literature around musical version identification (VI) research and co…
A Prototypical Triplet Loss for Cover Detection
Guillaume Doras, Geoffroy Peeters
Automatic cover detection -- the task of finding in a audio dataset all covers of a query track -- has long been a challenging theoretical problem in MIR community. It also became…
Cover Detection using Dominant Melody Embeddings
Guillaume Doras, Geoffroy Peeters
Automatic cover detection -- the task of finding in an audio database all the covers of one or several query tracks -- has long been seen as a challenging theoretical problem in th…