2.9k citations · 6k across the 15 of their papers we have counts for
8 papers · 1 filter
Large Scale GAN Training for High Fidelity Natural Image Synthesis
Andrew Brock, Jeff Donahue, Karen Simonyan
Despite recent progress in generative image modeling, successfully generating high-resolution, diverse samples from complex datasets such as ImageNet remains an elusive goal. To th…
This Time with Feeling: Learning Expressive Musical Performance
Sageev Oore, Ian Simon, Sander Dieleman +2
Music generation has generally been focused on either creating scores or interpreting them. We discuss differences between these two problems and propose that, in fact, it may be v…
The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman, Aäron van den Oord, Karen Simonyan
Realistic music generation is a challenging task. When building generative models of music that are learnt from data, typically high-level representations such as scores or MIDI ar…
DARTS: Differentiable Architecture Search
Hanxiao Liu, Karen Simonyan, Yiming Yang
This paper addresses the scalability challenge of architecture search by formulating the task in a differentiable manner. Unlike conventional approaches of applying evolution or re…
Learning to Navigate in Cities Without a Map
Piotr Mirowski, Matthew Koichi Grimes, Mateusz Malinowski +7
Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in the study and development of artificial intellig…
Kickstarting Deep Reinforcement Learning
Simon Schmitt, Jonathan J. Hudson, Augustin Zidek +8
We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and po…