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Stefan Lattner
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2020 – today
- 2024
- [c19]Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters:
Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning. ICASSP Workshops 2024: 680-684 - [c18]Marco Pasini, Maarten Grachten, Stefan Lattner:
Bass Accompaniment Generation Via Latent Diffusion. ICASSP 2024: 1166-1170 - [i31]Bernardo Torres, Stefan Lattner, Gaël Richard:
Singer Identity Representation Learning using Self-Supervised Techniques. CoRR abs/2401.05064 (2024) - [i30]Marco Pasini, Maarten Grachten, Stefan Lattner:
Bass Accompaniment Generation via Latent Diffusion. CoRR abs/2402.01412 (2024) - [i29]Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters:
Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning. CoRR abs/2405.08679 (2024) - [i28]Javier Nistal, Marco Pasini, Cyran Aouameur, Maarten Grachten, Stefan Lattner:
Diff-A-Riff: Musical Accompaniment Co-creation via Latent Diffusion Models. CoRR abs/2406.08384 (2024) - [i27]Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Michael Anslow, Geoffroy Peeters:
Stem-JEPA: A Joint-Embedding Predictive Architecture for Musical Stem Compatibility Estimation. CoRR abs/2408.02514 (2024) - [i26]Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer:
Controlling Surprisal in Music Generation via Information Content Curve Matching. CoRR abs/2408.06022 (2024) - [i25]Marco Pasini, Stefan Lattner, George Fazekas:
Music2Latent: Consistency Autoencoders for Latent Audio Compression. CoRR abs/2408.06500 (2024) - [i24]Emmanuel Deruty, David Meredith, Stefan Lattner:
The evolution of inharmonicity and noisiness in contemporary popular music. CoRR abs/2408.08127 (2024) - [i23]Javier Nistal, Marco Pasini, Stefan Lattner:
Improving Musical Accompaniment Co-creation via Diffusion Transformers. CoRR abs/2410.23005 (2024) - [i22]Marco Pasini, Javier Nistal, Stefan Lattner, George Fazekas:
Continuous Autoregressive Models with Noise Augmentation Avoid Error Accumulation. CoRR abs/2411.18447 (2024) - [i21]Alain Riou, Antonin Gagneré, Gaëtan Hadjeres, Stefan Lattner, Geoffroy Peeters:
Zero-shot Musical Stem Retrieval with Joint-Embedding Predictive Architectures. CoRR abs/2411.19806 (2024) - 2023
- [c17]Bernardo Torres, Stefan Lattner, Gaël Richard:
Singer Identity Representation Learning Using Self-Supervised Techniques. ISMIR 2023: 448-456 - [c16]Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters:
PESTO: Pitch Estimation With Self-Supervised Transposition-Equivariant Objective. ISMIR 2023: 535-544 - [c15]Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer:
Exploring Sampling Techniques for Generating Melodies With a Transformer Language Model. ISMIR 2023: 810-816 - [i20]Mathias Rose Bjare, Stefan Lattner, Gerhard Widmer:
Exploring Sampling Techniques for Generating Melodies with a Transformer Language Model. CoRR abs/2308.09454 (2023) - [i19]Alain Riou, Stefan Lattner, Gaëtan Hadjeres, Geoffroy Peeters:
PESTO: Pitch Estimation with Self-supervised Transposition-equivariant Objective. CoRR abs/2309.02265 (2023) - [i18]Marco Pasini, Stefan Lattner, George Fazekas:
Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates. CoRR abs/2311.13058 (2023) - 2022
- [j2]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): 35 (2022) - [j1]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): 190 (2022) - [c14]Stefan Lattner:
SampleMatch: Drum Sample Retrieval by Musical Context. ISMIR 2022: 781-788 - [i17]Javier Nistal, Cyran Aouameur, Ithan Velarde, Stefan Lattner:
DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks. CoRR abs/2206.14723 (2022) - [i16]Stefan Lattner, Javier Nistal:
Stochastic Restoration of Heavily Compressed Musical Audio using Generative Adversarial Networks. CoRR abs/2207.01667 (2022) - [i15]Stefan Lattner:
SampleMatch: Drum Sample Retrieval by Musical Context. CoRR abs/2208.01141 (2022) - [i14]Mathias Rose Bjare, Stefan Lattner:
On the Typicality of Musical Sequences. CoRR abs/2211.13016 (2022) - 2021
- [c13]Javier Nistal, Stefan Lattner, Gaël Richard:
DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis With GANs. ISMIR 2021: 484-492 - [c12]Javier Nistal, Cyran Aouameur, Stefan Lattner, Gaël Richard:
VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding. WASPAA 2021: 116-120 - [i13]Javier Nistal, Cyran Aouameur, Stefan Lattner, Gaël Richard:
VQCPC-GAN: Variable-length Adversarial Audio Synthesis using Vector-Quantized Contrastive Predictive Coding. CoRR abs/2105.01531 (2021) - [i12]Javier Nistal, Stefan Lattner, Gaël Richard:
DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis with GANs. CoRR abs/2108.01216 (2021) - 2020
- [c11]Javier Nistal, Stefan Lattner, Gaël Richard:
Comparing Representations for Audio Synthesis Using Generative Adversarial Networks. EUSIPCO 2020: 161-165 - [c10]Javier Nistal, Stefan Lattner, Gaël Richard:
DRUMGAN: Synthesis of Drum Sounds with Timbral Feature Conditioning Using Generative Adversarial Networks. ISMIR 2020: 590-597 - [i11]Stefan Lattner:
Modeling Musical Structure with Artificial Neural Networks. CoRR abs/2001.01720 (2020) - [i10]Javier Nistal, Stefan Lattner, Gaël Richard:
Comparing Representations for Audio Synthesis Using Generative Adversarial Networks. CoRR abs/2006.09266 (2020) - [i9]Javier Nistal, Stefan Lattner, Gaël Richard:
DrumGAN: Synthesis of Drum Sounds With Timbral Feature Conditioning Using Generative Adversarial Networks. CoRR abs/2008.12073 (2020)
2010 – 2019
- 2019
- [c9]Stefan Lattner, Monika Dörfler, Andreas Arzt:
Learning Complex Basis Functions for Invariant Representations of Audio. ISMIR 2019: 700-707 - [c8]Stefan Lattner, Maarten Grachten:
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. WASPAA 2019: 35-39 - [i8]Stefan Lattner, Monika Dörfler, Andreas Arzt:
Learning Complex Basis Functions for Invariant Representations of Audio. CoRR abs/1907.05982 (2019) - [i7]Stefan Lattner, Maarten Grachten:
High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. CoRR abs/1908.00948 (2019) - 2018
- [c7]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music based on Learned Interval Representations. ISMIR 2018: 26-33 - [c6]Andreas Arzt, Stefan Lattner:
Audio-to-Score Alignment using Transposition-invariant Features. ISMIR 2018: 592-599 - [c5]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Interval Representations from Polyphonic Music Sequences. ISMIR 2018: 661-668 - [i6]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Transposition-Invariant Interval Features from Symbolic Music and Audio. CoRR abs/1806.08236 (2018) - [i5]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
A Predictive Model for Music Based on Learned Interval Representations. CoRR abs/1806.08686 (2018) - [i4]Andreas Arzt, Stefan Lattner:
Audio-to-Score Alignment using Transposition-invariant Features. CoRR abs/1807.07278 (2018) - 2017
- [i3]Stefan Lattner, Maarten Grachten:
Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation. CoRR abs/1707.01357 (2017) - [i2]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Learning Musical Relations using Gated Autoencoders. CoRR abs/1708.05325 (2017) - 2016
- [i1]Stefan Lattner, Maarten Grachten, Gerhard Widmer:
Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints. CoRR abs/1612.04742 (2016) - 2015
- [c4]Kat Agres, Carlos Cancino, Maarten Grachten, Stefan Lattner:
A Computational Approach to Modelling the Perception of Pitch and Tonality in Music. CogSci 2015 - [c3]Stefan Lattner, Carlos Eduardo Cancino Chacón, Maarten Grachten:
Pseudo-Supervised Training Improves Unsupervised Melody Segmentation. IJCAI 2015: 2459-2465 - [c2]Stefan Lattner, Maarten Grachten, Kat Agres
Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines. MCM 2015: 323-334 - 2014
- [c1]Carlos Eduardo Cancino Chacón, Stefan Lattner, Maarten Grachten:
Developing Tonal Perception through Unsupervised Learning. ISMIR 2014: 195-200
Coauthor Index
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