Dani Valevski
Co-first author of GameNGen, a diffusion model that simulates DOOM in real time, and first author of UniTune
Dani Valevski is a co-first author of "Diffusion Models Are Real-Time Game Engines" (2024), which presents GameNGen, a neural model that interactively simulates the game DOOM in real time by training a diffusion model to predict the next frame from past frames and actions. The GameNGen project page lists Valevski with Google Research. Valevski is also first author of "UniTune: Text-Driven Image Editing by Fine Tuning a Diffusion Model on a Single Image" (2022).123
Work
GameNGen (Diffusion Models Are Real-Time Game Engines) (external site: gamengen.github.io)Published research
Co-first author, with Yaniv Leviathan, Moab Arar, and Shlomi Fruchter, of the 2024 paper; the project page describes training a reinforcement-learning agent to play DOOM and then a diffusion model that generates the next frame conditioned on past frames and actions.21
UniTune (external site: arxiv.org)Published research
First author, with Matan Kalman, Eyal Molad, Eyal Segalis, Yossi Matias, and Yaniv Leviathan, of the 2022 paper on text-driven editing of an image by fine-tuning a diffusion model on that single image.3
Other documented roles
Roles the sources document but that are not confirmed as current.
- Listed with Google Research as co-first author of GameNGen (2024), Google Research1
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.