Damien Vincent

According to our database, Damien Vincent authored at least 27 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

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, Neil Zeghidour, Andrea Agostinelli

CoRR, 2024

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

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, Eugene Kharitonov, Hannah Muckenhirn, Dirk Padfield, James Qin, Danny Rozenberg, Tara N. Sainath, Johan Schalkwyk, Matthew Sharifi, Michelle Tadmor Ramanovich, Marco Tagliasacchi, Alexandru Tudor, Mihajlo Velimirovic, Damien Vincent, Jiahui Yu, Yongqiang Wang, Vicky Zayats, Neil Zeghidour, Yu Zhang, Zhishuai Zhang, Lukas Zilka, Christian Havnø Frank

CoRR, 2023

SoundStorm: Efficient Parallel Audio Generation.

Zalán Borsos, Matthew Sharifi, Damien Vincent, Eugene Kharitonov, Neil Zeghidour, Marco Tagliasacchi

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, Matthew Sharifi, Marco Tagliasacchi, Neil Zeghidour

CoRR, 2023

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

Continuous Control with Action Quantization from Demonstrations.

Robert Dadashi, Léonard Hussenot, Damien Vincent, Sertan Girgin, Anton Raichuk, Matthieu Geist, Olivier Pietquin

Proceedings of the International Conference on Machine Learning, 2022

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

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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, Matthieu Geist, Olivier Pietquin

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Google Research Football: A Novel Reinforcement Learning Environment.

Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

MULEX: Disentangling Exploitation from Exploration in Deep RL.

Lucas Beyer, Damien Vincent, Olivier Teboul, Sylvain Gelly, Matthieu Geist, Olivier Pietquin

CoRR, 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, Gergely Neu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Episodic Curiosity through Reachability.

Nikolay Savinov, Anton Raichuk, Damien Vincent, Raphaël Marinier, Marc Pollefeys, Timothy P. Lillicrap, Sylvain Gelly

Proceedings of the 7th International Conference on Learning Representations, 2019

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

CoRR, 2018

Clustering Meets Implicit Generative Models.

Francesco Locatello, Damien Vincent, Ilya O. Tolstikhin, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf

Proceedings of the 6th International Conference on Learning Representations, 2018

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

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

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

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

Critical Hyper-Parameters: No Random, No Cry.

Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent

CoRR, 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

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

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Full Resolution Image Compression with Recurrent Neural Networks.

George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

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

Proceedings of the 4th International Conference on Learning Representations, 2016

2007

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

Proceedings of the IEEE International Conference on Acoustics, 2007

2006

Glottal Closure Instant Estimation using an Appropriateness Measure of the Source and Continuity Constraints.

Damien Vincent, Olivier Rosec, Thierry Chonavel

Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005

Estimation of LF glottal source parameters based on an ARX model.

Damien Vincent, Olivier Rosec, Thierry Chonavel

Proceedings of the INTERSPEECH 2005, 2005