I'm a fourth-year PhD student at Berkeley AI Research advised by Alyosha Efros.
Previously, I did my undergrad at MIT where I worked with
Antonio Torralba. I've interned at FAIR, Adobe Research and NVIDIA.
I'm supported by the National Science Foundation's Graduate Research Fellowship Program.
My research focuses on deep learning and artificial intelligence, with a strong emphasis on deep generative models.
I am especially interested in large-scale generative AI for synthesizing and manipulating visual content.
[Jan 2023] DiT is now natively usable in Hugging Face diffusers here. [Dec 2022] We released a DiT Hugging Face Space here. [Dec 2022] DiT code has been released in PyTorch here. [Sep 2022] G.pt code has been released in PyTorch here. [Jun 2022] GANgealing is a best paper finalist at CVPR'22. [Apr 2022] Check out Two Minute Papers' video covering GANgealing!
Learning to Learn with Generative Models of Neural Network Checkpoints William Peebles*, Ilija Radosavovic*, Tim Brooks, Alexei Efros, Jitendra Malik
project page ·
paper ·
github
The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement William Peebles, John Peebles, Jun-Yan Zhu, Alexei Efros, Antonio Torralba
ECCV 2020 (Spotlight)
video · overview in 90 seconds · project page · paper · github
Seeing What a GAN Cannot Generate David Bau, Jun-Yan Zhu, Jonas Wulff, William Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba
ICCV 2019 (Oral)
demo ·
project page ·
paper ·
github
Semantic Photo Manipulation with a Generative Image Prior David Bau, Hendrik Strobelt, William Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba
SIGGRAPH 2019 demo ·
project page ·
paper
