Stefan Lattner
Stefan Lattner
Sony CSL Paris, Associate Researcher
Verified email at stefanlattner.at
Title
Cited by
Cited by
Year
Imposing Higher-Level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints
S Lattner, M Grachten, G Widmer
Journal of Creative Music Systems 2 (2), 2018
632018
Audio-to-Score Alignment using Transposition-Invariant Features
A Arzt, S Lattner
19th International Society for Music Information Retrieval Conference (ISMIR …, 2018
132018
DrumGAN: Synthesis of drum sounds with timbral feature conditioning using Generative Adversarial Networks
J Nistal, S Lattner, G Richard
19th International Society for Music Information Retrieval Conference (ISMIR), 2020
112020
Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines
S Lattner, M Grachten, K Agres, CEC Chacón
International Conference on Mathematics and Computation in Music, 323-334, 2015
112015
A Predictive Model for Music Based on Learned Interval Representations
S Lattner, M Grachten, G Widmer
19th International Society for Music Information Retrieval Conference (ISMIR …, 2018
92018
Learning Transformations of Musical Material using Gated Autoencoders
S Lattner, M Grachten, G Widmer
Proceedings of the 2nd conference on computer simulation of musical …, 2017
9*2017
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio
S Lattner, M Grachten, G Widmer
19th International Society for Music Information Retrieval Conference (ISMIR …, 2018
82018
Hierarchical temporal memory-investigations, ideas, and experiments
S Lattner
Linz: Johannes Kepler Universität, Linz, Austria, 2014
82014
DrumNet: High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction
S Lattner, M Grachten
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics …, 2019
7*2019
Developing Tonal Perception through Unsupervised Learning
CEC Chacón, S Lattner, M Grachten
ISMIR 2014, 195-200, 2014
72014
Comparing representations for audio synthesis using generative adversarial networks
J Nistal, S Lattner, G Richard
27th European Signal Processing Conference (EUSIPCO) 2019, 2020
62020
Learning Complex Basis Functions for Invariant Representations of Audio
S Lattner, M Dörfler, A Arzt
20th International Society for Music Information Retrieval Conference (ISMIR …, 2019
42019
Harmonics co-occurrences bootstrap pitch and tonality perception in music: Evidence from a statistical unsupervised learning model
K Agres, C Cancino, M Grachten, S Lattner
Proceedings of the Cognitive Science Society, 2015
42015
Pseudo-supervised training improves unsupervised melody segmentation
S Lattner, CEC Chacón, M Grachten
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
32015
BassNet: A Variational Gated Autoencoder for Conditional Generation of Bass Guitar Tracks with Learned Interactive Control
M Grachten, S Lattner, E Deruty
Applied Sciences 10 (18), 6627, 2020
22020
Improving content-invariance in gated autoencoders for 2d and 3d object rotation
S Lattner, M Grachten
arXiv preprint arXiv:1707.01357, 2017
12017
VQCPC-GAN: Variable-length Adversarial Audio Synthesis using Vector-Quantized Contrastive Predictive Coding
J Nistal, C Aouameur, S Lattner, G Richard
arXiv preprint arXiv:2105.01531, 2021
2021
Stochastic Restoration of Heavily Compressed Musical Audio Using Generative Adversarial Networks
S Lattner, J Nistal
Electronics 10 (11), 1349, 2021
2021
Modeling Musical Structure with Artificial Neural Networks
S Lattner
PhD thesis, Johannes Kepler University, Linz, 2019
2019
A Computational Approach to Modelling the Perception of Pitch and Tonality in Music.
K Agres, C Cancino, M Grachten, S Lattner
CogSci, 2015
2015
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Articles 1–20