125 citations · 245 across the 22 of their papers we have counts for
4 papers · 1 filter
Interactive Music Generation with Positional Constraints using Anticipation-RNNs
Gaëtan Hadjeres, Frank Nielsen
Recurrent Neural Networks (RNNS) are now widely used on sequence generation tasks due to their ability to learn long-range dependencies and to generate sequences of arbitrary lengt…
Deep rank-based transposition-invariant distances on musical sequences
Gaëtan Hadjeres, Frank Nielsen
Distances on symbolic musical sequences are needed for a variety of applications, from music retrieval to automatic music generation. These musical sequences belong to a given corp…
Deep Learning Techniques for Music Generation -- A Survey
Jean-Pierre Briot, Gaëtan Hadjeres, François-David Pachet
This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content. We propose a methodology based on fiv…
GLSR-VAE: Geodesic Latent Space Regularization for Variational AutoEncoder Architectures
Gaëtan Hadjeres, Frank Nielsen, François Pachet
VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes. In many settings, t…