Speaker
Vinicius Massami Mikuni
(Lawrence Berkeley National Lab. (US))
Description
Diffusion generative models are a recent type of generative models that excel in various tasks, including those in collider physics and beyond. Thanks to their stable training and flexibility, these models can easily incorporate symmetries to better represent the data they generate. In this talk, I will provide an overview of diffusion models' key features and highlight their practical applications in collider physics based on recent works, such as fast detector simulation, jet generation, direct density estimation, and anomaly detection of new physics processes.
Authors
Ben Nachman
(Lawrence Berkeley National Lab. (US))
Vinicius Massami Mikuni
(Lawrence Berkeley National Lab. (US))
