2k citations · 4.6k across the 27 of their papers we have counts for
10 papers · 1 filter
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning
Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan +21
StarCraft II is one of the most challenging simulated reinforcement learning environments; it is partially observable, stochastic, multi-agent, and mastering StarCraft II requires…
Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi +3
Recent developments in the field of model-based RL have proven successful in a range of environments, especially ones where planning is essential. However, such successes have been…
Low Bit-Rate Speech Coding with VQ-VAE and a WaveNet Decoder
Cristina Gârbacea, Aäron van den Oord, Yazhe Li +4
In order to efficiently transmit and store speech signals, speech codecs create a minimally redundant representation of the input signal which is then decoded at the receiver with…
Shaping Belief States with Generative Environment Models for RL
Karol Gregor, Danilo Jimenez Rezende, Frederic Besse +3
When agents interact with a complex environment, they must form and maintain beliefs about the relevant aspects of that environment. We propose a way to efficiently train expressiv…
On Variational Bounds of Mutual Information
Ben Poole, Sherjil Ozair, Aaron van den Oord +2
Estimating and optimizing Mutual Information (MI) is core to many problems in machine learning; however, bounding MI in high dimensions is challenging. To establish tractable and s…
Wasserstein Dependency Measure for Representation Learning
Sherjil Ozair, Corey Lynch, Yoshua Bengio +3
Mutual information maximization has emerged as a powerful learning objective for unsupervised representation learning obtaining state-of-the-art performance in applications such as…
Preventing Posterior Collapse with delta-VAEs
Ali Razavi, Aäron van den Oord, Ben Poole +1
Due to the phenomenon of "posterior collapse," current latent variable generative models pose a challenging design choice that either weakens the capacity of the decoder or require…
Sample Efficient Adaptive Text-to-Speech
Yutian Chen, Yannis Assael, Brendan Shillingford +11
We present a meta-learning approach for adaptive text-to-speech (TTS) with few data. During training, we learn a multi-speaker model using a shared conditional WaveNet core and ind…
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Jonathan Uesato, Brendan O'Donoghue, Aaron van den Oord +1
This paper investigates recently proposed approaches for defending against adversarial examples and evaluating adversarial robustness. We motivate 'adversarial risk' as an objectiv…
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
Aaron van den Oord, Yazhe Li, Igor Babuschkin +19
The recently-developed WaveNet architecture is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages…