Prafulla Dhariwal
Research scientist at OpenAI; co-author of Diffusion Models Beat GANs, GLIDE, Jukebox, and Glow
Prafulla Dhariwal is a research scientist at OpenAI working on generative models and unsupervised learning. Dhariwal is co-first author, with Alex Nichol, of "Improved Denoising Diffusion Probabilistic Models" and "Diffusion Models Beat GANs on Image Synthesis", whose MIT-licensed OpenAI codebases release checkpoints for the papers' main models, and a co-first author of GLIDE. Dhariwal is also first author of Jukebox, a generative model for music, and co-first author with Diederik P. Kingma of Glow. With Yang Song, Dhariwal co-authored the consistency models papers, whose PyTorch code OpenAI publishes under the MIT license.1231245678911
Work
Guided diffusion (Diffusion Models Beat GANs on Image Synthesis) (external site: github.com)Open-source code
Co-first author with Alex Nichol of the 2021 paper. The openai/guided-diffusion repository is the paper's codebase, builds on openai/improved-diffusion from the pair's Improved DDPM paper, releases checkpoints for the main models, and is licensed under the MIT License.3245
Jukebox (external site: arxiv.org)Published research
First author of "Jukebox: A Generative Model for Music" (2020), with Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, and Ilya Sutskever.71
Consistency models (external site: github.com)Open-source code
Co-author with Yang Song, Mark Chen, and Ilya Sutskever of "Consistency Models" (2023) and, with Yang Song, of "Improved Techniques for Training Consistency Models" (2023). The openai repository releases code and checkpoints under the MIT License.91011
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