We are always happy to have PhD interns on the team. If you are a PhD student interested in our activities, feel free to contact us!


ICCC 2019
Neural Drum Machine: An Interactive System for Real-time Synthesis of Drum Sounds
Cyran Aouameur, Philippe Esling, Gaëtan Hadjeres
VAE, drum synthesis, controlable system, latent space exploration
Variation Network: Learning High-level Attributes for Controlled Input Manipulation
Gaëtan Hadjeres, Frank Nielsen
VAE, latent space disentanglement, adversarial learning
On power chi expansions of f-divergences
Frank Nielsen, Gaëtan Hadjeres
f-divergences, chi-squared distance, exponential family, Taylor expansions, binomial and multinomial theorems, analytic formula, bounded density ratio
ISMIR 2018
A Predictive Model for Music Based on Learned Interval Representations
Stefan Lattner, Maarten Grachten, Gerhard Widmer
recurrent gated autoencoder, relative pitch modelling, interval representation
ISMIR 2018
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio
Stefan Lattner, Maarten Grachten, Gerhard Widmer
repeated sections discovery, interval representation, transposition invariance
ISMIR 2018
Audio-to-Score Alignment using Transposition-invariant Features
Andreas Arzt, Stefan Lattner
audio-to-score alignment, gated autoencoder, local pitch intervals, transposition invariance
Neural Computing and Applications 2018
Anticipation-RNN: Enforcing Unary Constraints in Sequence Generation, with Application to Interactive Music Generation
Gaëtan Hadjeres, Frank Nielsen
automatic symbolic music generation, recurrent neural networks, interactive models, unary constraints
SSCI 2017
GLSR-VAE: Geodesic Latent Space Regularization for Variational Autoencoder Architectures
Gaëtan Hadjeres, François Pachet, Frank Nielsen
VAE, latent space regularization, disentaglement
ICML 2017
DeepBach: a Steerable Model for Bach Chorales Generation
Gaëtan Hadjeres, François Pachet, Frank Nielsen
musical inpainting, Bach chorales