Estimation of LF glottal source parameters based on an ARX model. - Damien Vincent; Olivier Rosec; Thierry Chonavel (INTERSPEECH, 2005)

Glottal Closure Instant Estimation using an Appropriateness Measure of the Source and Continuity Constraints. - Damien Vincent; Olivier Rosec; Thierry Chonavel (ICASSP (1), 2006)

A New Method for Speech Synthesis and Transformation Based on an ARX-LF Source-Filter Decomposition and HNM Modeling. - Damien Vincent; Olivier Rosec; Thierry Chonavel (ICASSP (4), 2007)

Variable Rate Image Compression with Recurrent Neural Networks. - George Toderici; Sean M. O'Malley; Sung Jin Hwang; Damien Vincent; David Minnen; Shumeet Baluja; Michele Covell; Rahul Sukthankar (ICLR (Poster), 2016)

Full Resolution Image Compression with Recurrent Neural Networks. - George Toderici; Damien Vincent; Nick Johnston; Sung Jin Hwang; David Minnen; Joel Shor; Michele Covell (CVPR, 2017)

Spatially adaptive image compression using a tiled deep network. - David Minnen; George Toderici; Michele Covell; Troy T. Chinen; Nick Johnston; Joel Shor; Sung Jin Hwang; Damien Vincent; Saurabh Singh (ICIP, 2017)

Toward Optimal Run Racing: Application to Deep Learning Calibration. - Olivier Bousquet; Sylvain Gelly; Karol Kurach; Marc Schoenauer; Michèle Sebag; Olivier Teytaud; Damien Vincent (CoRR, 2017)

Critical Hyper-Parameters: No Random, No Cry. - Olivier Bousquet; Sylvain Gelly; Karol Kurach; Olivier Teytaud; Damien Vincent (CoRR, 2017)

Target-Quality Image Compression with Recurrent, Convolutional Neural Networks. - Michele Covell; Nick Johnston; David Minnen; Sung Jin Hwang; Joel Shor; Saurabh Singh; Damien Vincent; George Toderici (CoRR, 2017)

Better Text Understanding Through Image-To-Text Transfer. - Karol Kurach; Sylvain Gelly; Michal Jastrzebski; Philip Häusser; Olivier Teytaud; Damien Vincent; Olivier Bousquet (CoRR, 2017)

Improved Lossy Image Compression With Priming and Spatially Adaptive Bit Rates for Recurrent Networks. - Nick Johnston; Damien Vincent; David Minnen; Michele Covell; Saurabh Singh; Troy T. Chinen; Sung Jin Hwang; Joel Shor; George Toderici (CVPR, 2018)

Clustering Meets Implicit Generative Models. - Francesco Locatello; Damien Vincent; Ilya O. Tolstikhin; Gunnar Rätsch; Sylvain Gelly; Bernhard Schölkopf (ICLR (Workshop), 2018)

Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem. - Hugo Penedones; Damien Vincent; Hartmut Maennel; Sylvain Gelly; Timothy A. Mann; André Barreto 001 (CoRR, 2018)

Episodic Curiosity through Reachability. - Nikolay Savinov; Anton Raichuk; Damien Vincent; Raphaël Marinier; Marc Pollefeys; Timothy P. Lillicrap; Sylvain Gelly (ICLR (Poster), 2019)

Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. - Carlos Riquelme; Hugo Penedones; Damien Vincent; Hartmut Maennel; Sylvain Gelly; Timothy A. Mann; André Barreto 001; Gergely Neu (NeurIPS, 2019)

MULEX: Disentangling Exploitation from Exploration in Deep RL. - Lucas Beyer; Damien Vincent; Olivier Teboul; Sylvain Gelly; Matthieu Geist; Olivier Pietquin (CoRR, 2019)

Google Research Football: A Novel Reinforcement Learning Environment. - Karol Kurach; Anton Raichuk; Piotr Stanczyk; Michal Zajac 005; Olivier Bachem; Lasse Espeholt; Carlos Riquelme; Damien Vincent; Marcin Michalski; Olivier Bousquet; Sylvain Gelly (AAAI, 2020)

Hyperparameter Selection for Imitation Learning. - Léonard Hussenot; Marcin Andrychowicz; Damien Vincent; Robert Dadashi; Anton Raichuk; Sabela Ramos; Nikola Momchev; Sertan Girgin; Raphaël Marinier; Lukasz Stafiniak; Manu Orsini; Olivier Bachem; et al. (ICML, 2021)

What Matters for Adversarial Imitation Learning? - Manu Orsini; Anton Raichuk; Léonard Hussenot; Damien Vincent; Robert Dadashi; Sertan Girgin; Matthieu Geist; Olivier Bachem; Olivier Pietquin; Marcin Andrychowicz (NeurIPS, 2021)

RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning. - Sabela Ramos; Sertan Girgin; Léonard Hussenot; Damien Vincent; Hanna Yakubovich; Daniel Toyama; Anita Gergely; Piotr Stanczyk; Raphaël Marinier; Jeremiah Harmsen; Olivier Pietquin; Nikola Momchev (CoRR, 2021)

Continuous Control with Action Quantization from Demonstrations. - Robert Dadashi; Léonard Hussenot; Damien Vincent; Sertan Girgin; Anton Raichuk; Matthieu Geist; Olivier Pietquin (ICML, 2022)

AudioLM: a Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (CoRR, 2022)

SoundStorm: Efficient Parallel Audio Generation. - Zalán Borsos; Matthew Sharifi; Damien Vincent; Eugene Kharitonov; Neil Zeghidour; Marco Tagliasacchi (CoRR, 2023)

AudioPaLM: A Large Language Model That Can Speak and Listen. - Paul K. Rubenstein; Chulayuth Asawaroengchai; Duc Dung Nguyen; Ankur Bapna; Zalán Borsos; Félix de Chaumont Quitry; Peter Chen; Dalia El Badawy; Wei Han 002; Eugene Kharitonov; Hannah Muckenhirn; Dirk Padfield; et al. (CoRR, 2023)

Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision. - Eugene Kharitonov; Damien Vincent; Zalán Borsos; Raphaël Marinier; Sertan Girgin; Olivier Pietquin; Matt Sharifi; Marco Tagliasacchi; Neil Zeghidour (Trans. Assoc. Comput. Linguistics, 2023)

AudioLM: A Language Modeling Approach to Audio Generation. - Zalán Borsos; Raphaël Marinier; Damien Vincent; Eugene Kharitonov; Olivier Pietquin; Matthew Sharifi; Dominik Roblek; Olivier Teboul; David Grangier; Marco Tagliasacchi; Neil Zeghidour (IEEE ACM Trans. Audio Speech Lang. Process., 2023)

MusicRL: Aligning Music Generation to Human Preferences. - Geoffrey Cideron; Sertan Girgin; Mauro Verzetti; Damien Vincent; Matej Kastelic; Zalán Borsos; Brian McWilliams; Victor Ungureanu; Olivier Bachem; Olivier Pietquin; Matthieu Geist; Léonard Hussenot; et al. (ICML, 2024)