activity
20182023
most citedTowards Accurate Generative Models of Video: A New Metric & Challenges

190 citations · 531 across the 8 of their papers we have counts for

collaborators

9 papers

cs.SD2023★ 3 cited

Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision

Eugene Kharitonov, Damien Vincent, Zalán Borsos +6

We introduce SPEAR-TTS, a multi-speaker text-to-speech (TTS) system that can be trained with minimal supervision. By combining two types of discrete speech representations, we cast…

cs.SD2022★ 24 cited

AudioLM: a Language Modeling Approach to Audio Generation

Zalán Borsos, Raphaël Marinier, Damien Vincent +8

We introduce AudioLM, a framework for high-quality audio generation with long-term consistency. AudioLM maps the input audio to a sequence of discrete tokens and casts audio genera…

cs.LG2021★ 3 cited

RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning

Sabela Ramos, Sertan Girgin, Léonard Hussenot +9

We introduce RLDS (Reinforcement Learning Datasets), an ecosystem for recording, replaying, manipulating, annotating and sharing data in the context of Sequential Decision Making (…

math.DS2021

Solving N-player dynamic routing games with congestion: a mean field approach

Theophile Cabannes, Mathieu Lauriere, Julien Perolat +7

The recent emergence of navigational tools has changed traffic patterns and has now enabled new types of congestion-aware routing control like dynamic road pricing. Using the funda…

cs.LG2021★ 7 cited

Hyperparameter Selection for Imitation Learning

Leonard Hussenot, Marcin Andrychowicz, Damien Vincent +11

We address the issue of tuning hyperparameters (HPs) for imitation learning algorithms in the context of continuous-control, when the underlying reward function of the demonstratin…

cs.LG2020★ 107 cited

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

Marcin Andrychowicz, Anton Raichuk, Piotr Stańczyk +9

In recent years, on-policy reinforcement learning (RL) has been successfully applied to many different continuous control tasks. While RL algorithms are often conceptually simple,…