Machine Learning

Anticipatory Music Transformer
We introduce anticipation: a method for constructing a controllable generative model of a temporal point process (the event process) …
John Thickstun, David Hall, Chris Donahue, Percy Liang
arXiv PDF BibTeX 🔊 Examples Code
It's Raw! Audio Generation with State-Space Models
Developing architectures suitable for modeling raw audio is a challenging problem due to the high sampling rates of audio waveforms. …
Karan Goel, Albert Gu, Chris Donahue, Christopher Ré
arXiv PDF BibTeX 🔊 Examples Code
Adversarial Audio Synthesis
Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of …
Chris Donahue, Julian McAuley, Miller Puckette
arXiv PDF BibTeX 🔊 Examples Code 🕹️ Demo Notebook
Piano Genie
We present Piano Genie, an intelligent controller which allows non-musicians to improvise on the piano. With Piano Genie, a user …
Chris Donahue, Ian Simon, Sander Dieleman
arXiv PDF BibTeX Code 🕹️ Demo Video Blog
Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
We propose a new algorithm for training generative adversarial networks that jointly learns latent codes for both identities (e.g. …
Chris Donahue, Zachary C. Lipton, Akshay Balsubramani, Julian McAuley
arXiv PDF BibTeX Code 🕹️ Demo
Dance Dance Convolution
Dance Dance Revolution (DDR) is a popular rhythm-based video game. Players perform steps on a dance platform in synchronization with …
Chris Donahue, Zachary C. Lipton, Julian McAuley
arXiv PDF BibTeX Code Dataset 🕹️ Demo