Diederik P. Kingma
Researcher at Anthropic; first author of the Variational Autoencoder and Adam optimizer papers
Diederik P. (Durk) Kingma has worked on research on large-scale machine learning at Anthropic since 2024. From 2018 to 2024 Kingma was a Research Scientist at Google Brain and Google DeepMind, where Kingma led research projects on generative models for text, image, and video, and from 2015 to 2018 Kingma was part of OpenAI's founding team and a Research Scientist there who led the Algorithms team. Kingma is first author of "Auto-Encoding Variational Bayes", which introduced the Variational Autoencoder, and of "Adam: A Method for Stochastic Optimization" with Jimmy Ba; ICLR named the two papers the winners of its 2024 and 2025 Test of Time awards. Kingma's other work includes Glow, with Prafulla Dhariwal, and Variational Diffusion Models.1234567
Work
Variational Autoencoder (Auto-Encoding Variational Bayes) (external site: arxiv.org)Published research
First author, with Max Welling, of the 2013 paper that introduced the Variational Autoencoder; winner of the inaugural ICLR Test of Time award in 2024.241
Adam optimizer (external site: arxiv.org)Published research
First author, with Jimmy Ba, of "Adam: A Method for Stochastic Optimization" (2014); winner of the ICLR 2025 Test of Time award.351
Glow and Variational Diffusion Models (external site: arxiv.org)Published research
Co-first author with Prafulla Dhariwal of "Glow: Generative Flow with Invertible 1x1 Convolutions" (2018) and first author, with Tim Salimans, Ben Poole, and Jonathan Ho, of "Variational Diffusion Models" (2021).671
Other documented roles
Roles the sources document but that are not confirmed as current.
- Research Scientist (2018–2024), Google Brain / Google DeepMind1
- Founding team member and Research Scientist (2015–2018); led the Algorithms team, OpenAI1
This profile covers public professional work only, from the sources below. It is not an endorsement or a ranking. To correct or remove it, use the correction form.