Postdoc, Los Alamos National Laboratory
1 paper at NeurIPS 2025
This paper presents Discrete Spatial Diffusion, a generative model for discrete-state data that ensures mass conservation, enabling applications in scientific domains like materials science, also demonstrating results on popular image benchmarks.
