Developing Tonal Perception through Unsupervised Learning. - Carlos Eduardo Cancino Chacón; Stefan Lattner; Maarten Grachten (ISMIR, 2014)

A Computational Approach to Modelling the Perception of Pitch and Tonality in Music. - Kat Agres; Carlos Cancino; Maarten Grachten; Stefan Lattner (CogSci, 2015)

Pseudo-Supervised Training Improves Unsupervised Melody Segmentation. - Stefan Lattner; Carlos Eduardo Cancino Chacón; Maarten Grachten (IJCAI, 2015)

Probabilistic Segmentation of Musical Sequences Using Restricted Boltzmann Machines. - Stefan Lattner; Maarten Grachten; Kat Agres; Carlos Eduardo Cancino Chacón (MCM, 2015)

Imposing higher-level Structure in Polyphonic Music Generation using Convolutional Restricted Boltzmann Machines and Constraints. - Stefan Lattner; Maarten Grachten; Gerhard Widmer (CoRR, 2016)

Improving Content-Invariance in Gated Autoencoders for 2D and 3D Object Rotation. - Stefan Lattner; Maarten Grachten (CoRR, 2017)

Learning Musical Relations using Gated Autoencoders. - Stefan Lattner; Maarten Grachten; Gerhard Widmer (CoRR, 2017)

Audio-to-Score Alignment using Transposition-invariant Features. - Andreas Arzt; Stefan Lattner (ISMIR, 2018)

A Predictive Model for Music based on Learned Interval Representations. - Stefan Lattner; Maarten Grachten; Gerhard Widmer (ISMIR, 2018)

Learning Interval Representations from Polyphonic Music Sequences. - Stefan Lattner; Maarten Grachten; Gerhard Widmer (ISMIR, 2018)

Learning Transposition-Invariant Interval Features from Symbolic Music and Audio. - Stefan Lattner; Maarten Grachten; Gerhard Widmer (CoRR, 2018)

Learning Complex Basis Functions for Invariant Representations of Audio. - Stefan Lattner; Monika Dörfler; Andreas Arzt (ISMIR, 2019)

High-Level Control of Drum Track Generation Using Learned Patterns of Rhythmic Interaction. - Stefan Lattner; Maarten Grachten (WASPAA, 2019)

Comparing Representations for Audio Synthesis Using Generative Adversarial Networks. - Javier Nistal; Stefan Lattner; Gaël Richard (EUSIPCO, 2020)

DRUMGAN: Synthesis of Drum Sounds with Timbral Feature Conditioning Using Generative Adversarial Networks. - Javier Nistal; Stefan Lattner; Gaël Richard (ISMIR, 2020)

Modeling Musical Structure with Artificial Neural Networks. - Stefan Lattner (CoRR, 2020)

DarkGAN: Exploiting Knowledge Distillation for Comprehensible Audio Synthesis With GANs. - Javier Nistal; Stefan Lattner; Gaël Richard (ISMIR, 2021)

VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding. - Javier Nistal; Cyran Aouameur; Stefan Lattner; Gaël Richard (WASPAA, 2021)

SampleMatch: Drum Sample Retrieval by Musical Context. - Stefan Lattner (ISMIR, 2022)

DrumGAN VST: A Plugin for Drum Sound Analysis/Synthesis With Autoencoding Generative Adversarial Networks. - Javier Nistal; Cyran Aouameur; Ithan Velarde; Stefan Lattner (CoRR, 2022)

Stochastic Restoration of Heavily Compressed Musical Audio using Generative Adversarial Networks. - Stefan Lattner; Javier Nistal (CoRR, 2022)

On the Typicality of Musical Sequences. - Mathias Rose Bjare; Stefan Lattner (CoRR, 2022)

Differentiable Short-Term Models for Efficient Online Learning and Prediction in Monophonic Music. - Mathias Rose Bjare; Stefan Lattner; Gerhard Widmer (Trans. Int. Soc. Music. Inf. Retr., 2022)

On the Development and Practice of AI Technology for Contemporary Popular Music Production. - Emmanuel Deruty; Maarten Grachten; Stefan Lattner; Javier Nistal; Cyran Aouameur (Trans. Int. Soc. Music. Inf. Retr., 2022)

Exploring Sampling Techniques for Generating Melodies With a Transformer Language Model. - Mathias Rose Bjare; Stefan Lattner; Gerhard Widmer (ISMIR, 2023)

PESTO: Pitch Estimation With Self-Supervised Transposition-Equivariant Objective. - Alain Riou; Stefan Lattner; Gaëtan Hadjeres; Geoffroy Peeters (ISMIR, 2023)

Singer Identity Representation Learning Using Self-Supervised Techniques. - Bernardo Torres; Stefan Lattner; Gaël Richard (ISMIR, 2023)

Self-Supervised Music Source Separation Using Vector-Quantized Source Category Estimates. - Marco Pasini; Stefan Lattner; George Fazekas (CoRR, 2023)

Bass Accompaniment Generation Via Latent Diffusion. - Marco Pasini; Maarten Grachten; Stefan Lattner (ICASSP, 2024)

Investigating Design Choices in Joint-Embedding Predictive Architectures for General Audio Representation Learning. - Alain Riou; Stefan Lattner; Gaëtan Hadjeres; Geoffroy Peeters (ICASSP Workshops, 2024)

Controlling Surprisal in Music Generation via Information Content Curve Matching. - Mathias Rose Bjare; Stefan Lattner; Gerhard Widmer (ISMIR, 2024)

Diff-a-Riff: Musical Accompaniment Co-Creation via Latent Diffusion Models. - Javier Nistal; Marco Pasini; Cyran Aouameur; Maarten Grachten; Stefan Lattner (ISMIR, 2024)

Music2Latent: Consistency Autoencoders for Latent Audio Compression. - Marco Pasini; Stefan Lattner; George Fazekas (ISMIR, 2024)

Stem-JEPA: A Joint-Embedding Predictive Architecture for Musical Stem Compatibility Estimation. - Alain Riou; Stefan Lattner; Gaëtan Hadjeres; Michael Anslow; Geoffroy Peeters (ISMIR, 2024)

The evolution of inharmonicity and noisiness in contemporary popular music. - Emmanuel Deruty; David Meredith 001; Stefan Lattner (CoRR, 2024)

Improving Musical Accompaniment Co-creation via Diffusion Transformers. - Javier Nistal; Marco Pasini; Stefan Lattner (CoRR, 2024)

Continuous Autoregressive Models with Noise Augmentation Avoid Error Accumulation. - Marco Pasini; Javier Nistal; Stefan Lattner; George Fazekas (CoRR, 2024)

Estimating Musical Surprisal in Audio. - Mathias Rose Bjare; Giorgia Cantisani; Stefan Lattner; Gerhard Widmer (ICASSP, 2025)

Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decoding. - Marco Pasini; Stefan Lattner; György Fazekas (ICASSP, 2025)

Zero-shot Musical Stem Retrieval with Joint-Embedding Predictive Architectures. - Alain Riou; Antonin Gagneré; Gaëtan Hadjeres; Stefan Lattner; Geoffroy Peeters (ICASSP, 2025)

Hybrid Losses for Hierarchical Embedding Learning. - Haokun Tian; Stefan Lattner; Brian McFee; Charalampos Saitis (ICASSP, 2025)

Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decoding. - Marco Pasini; Stefan Lattner; George Fazekas (CoRR, 2025)

Assessing the Alignment of Audio Representations with Timbre Similarity Ratings. - Haokun Tian; Stefan Lattner; Charalampos Saitis (CoRR, 2025)