Stefan Lattner

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 43

Top Topics

Diffusion Models

Polyphonic Music

Supervised Training

Artificial Neural Networks

Top Venues

Trans. Int. Soc. Music. Inf. Retr.

Publications

Javier Nistal, Marco Pasini, Cyran Aouameur, Maarten Grachten, Stefan Lattner
Diff-A-Riff: Musical Accompaniment Co-creation via Latent Diffusion Models. CoRR (2024)
Bernardo Torres, Stefan Lattner, Gaël Richard
Singer Identity Representation Learning using Self-Supervised Techniques. CoRR (2024)
Marco Pasini, Maarten Grachten, Stefan Lattner
Bass Accompaniment Generation Via Latent Diffusion. ICASSP (2024)
Marco Pasini, Maarten Grachten, Stefan Lattner
Bass Accompaniment Generation via Latent Diffusion. CoRR (2024)
Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters
Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning. CoRR (2024)
Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer
Exploring Sampling Techniques for Generating Melodies With a Transformer Language Model. ISMIR (2023)
Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters
PESTO: Pitch Estimation With Self-Supervised Transposition-Equivariant Objective. ISMIR (2023)
Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer
Exploring Sampling Techniques for Generating Melodies with a Transformer Language Model. CoRR (2023)
Marco Pasini, Stefan Lattner, George Fazekas
Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates. CoRR (2023)
Bernardo Torres, Stefan Lattner, Gaël Richard
Singer Identity Representation Learning Using Self-Supervised Techniques. ISMIR (2023)
Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters
PESTO: Pitch Estimation with Self-supervised Transposition-equivariant Objective. CoRR (2023)
Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer
Differentiable Short-Term Models for Efficient Online Learning and Prediction in Monophonic Music. Trans. Int. Soc. Music. Inf. Retr. 5 (1) (2022)
Emmanuel Deruty, Maarten Grachten, Stefan Lattner, Javier Nistal, Cyran Aouameur
On the Development and Practice of AI Technology for Contemporary Popular Music Production. Trans. Int. Soc. Music. Inf. Retr. 5 (1) (2022)
Stefan Lattner, Javier Nistal
Stochastic Restoration of Heavily Compressed Musical Audio using Generative Adversarial Networks. CoRR (2022)
Mathias Rose Bjare, Stefan Lattner
On the Typicality of Musical Sequences. CoRR (2022)
Stefan Lattner
SampleMatch: Drum Sample Retrieval by Musical Context. ISMIR (2022)
Javier Nistal, Cyran Aouameur, Ithan Velarde, Stefan Lattner
DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks. CoRR (2022)
Stefan Lattner
SampleMatch: Drum Sample Retrieval by Musical Context. CoRR (2022)
Javier Nistal, Cyran Aouameur, Stefan Lattner, Gaël Richard
VQCPC-GAN: Variable-length Adversarial Audio Synthesis using Vector-Quantized Contrastive Predictive Coding. CoRR (2021)
Javier Nistal, Stefan Lattner, Gaël Richard
DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis With GANs. ISMIR (2021)
Javier Nistal, Cyran Aouameur, Stefan Lattner, Gaël Richard
VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding. WASPAA (2021)
Javier Nistal, Stefan Lattner, Gaël Richard
DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs. CoRR (2021)
Javier Nistal, Stefan Lattner, Gaël Richard
DrumGAN: Synthesis of Drum Sounds With Timbral Feature Conditioning Using Generative Adversarial Networks. CoRR (2020)
Javier Nistal, Stefan Lattner, Gaël Richard
Comparing Representations for Audio Synthesis Using Generative Adversarial Networks. CoRR (2020)
Stefan Lattner
Modeling Musical Structure with Artificial Neural Networks. CoRR (2020)
Javier Nistal, Stefan Lattner, Gaël Richard
DRUMGAN: Synthesis of Drum Sounds with Timbral Feature Conditioning Using Generative Adversarial Networks. ISMIR (2020)
Javier Nistal, Stefan Lattner, Gaël Richard
Comparing Representations for Audio Synthesis Using Generative Adversarial Networks. EUSIPCO (2020)
Stefan Lattner, Monika Dörfler, Andreas Arzt
Learning Complex Basis Functions for Invariant Representations of Audio. ISMIR (2019)
Stefan Lattner, Maarten Grachten
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. WASPAA (2019)
Stefan Lattner, Monika Dörfler, Andreas Arzt
Learning Complex Basis Functions for Invariant Representations of Audio. CoRR (2019)
Stefan Lattner, Maarten Grachten
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. CoRR (2019)
Andreas Arzt, Stefan Lattner
Audio-to-Score Alignment using Transposition-invariant Features. ISMIR (2018)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio. CoRR (2018)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
A Predictive Model for Music based on Learned Interval Representations. ISMIR (2018)
Andreas Arzt, Stefan Lattner
Audio-to-Score Alignment using Transposition-invariant Features. CoRR (2018)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
A Predictive Model for Music Based on Learned Interval Representations. CoRR (2018)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
Learning Interval Representations from Polyphonic Music Sequences. ISMIR (2018)
Stefan Lattner, Maarten Grachten
Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation. CoRR (2017)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
Learning Musical Relations using Gated Autoencoders. CoRR (2017)
Stefan Lattner, Maarten Grachten, Gerhard Widmer
Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints. CoRR (2016)
Stefan Lattner, Maarten Grachten, Kat Agres, Carlos Eduardo Cancino Chacón
Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines. MCM (2015)
Kat Agres, Carlos Cancino, Maarten Grachten, Stefan Lattner
A Computational Approach to Modelling the Perception of Pitch and Tonality in Music. CogSci (2015)
Stefan Lattner, Carlos Eduardo Cancino Chacón, Maarten Grachten
Pseudo-Supervised Training Improves Unsupervised Melody Segmentation. IJCAI (2015)
Carlos Eduardo Cancino Chacón, Stefan Lattner, Maarten Grachten
Developing Tonal Perception through Unsupervised Learning. ISMIR (2014)