ν-Flows: Conditional Neutrino Regression. - Matthew Leigh; John Andrew Raine; Knut Zoch; Tobias Golling (CoRR, 2022)

PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics. - Matthew Leigh; Debajyoti Sengupta; Guillaume Quétant; John Andrew Raine; Knut Zoch; Tobias Golling (CoRR, 2023)

ν2-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows. - John Andrew Raine; Matthew Leigh; Knut Zoch; Tobias Golling (CoRR, 2023)

PC-Droid: Faster diffusion and improved quality for particle cloud generation. - Matthew Leigh; Debajyoti Sengupta; John Andrew Raine; Guillaume Quétant; Tobias Golling (CoRR, 2023)

EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion. - Erik Buhmann; Cedric Ewen; Darius A. Faroughy; Tobias Golling; Gregor Kasieczka; Matthew Leigh; Guillaume Quétant; John Andrew Raine; Debajyoti Sengupta; David Shih (CoRR, 2023)

Improving new physics searches with diffusion models for event observables and jet constituents. - Debajyoti Sengupta; Matthew Leigh; John Andrew Raine; Samuel Klein; Tobias Golling (CoRR, 2023)

PIPPIN: Generating variable length full events from partons. - Guillaume Quétant; John Andrew Raine; Matthew Leigh; Debajyoti Sengupta; Tobias Golling (CoRR, 2024)

Is Tokenization Needed for Masked Particle Modelling? - Matthew Leigh; Samuel Klein; François Charton; Tobias Golling; Lukas Heinrich; Michael Kagan; Inês Ochoa; Margarita Osadchy (CoRR, 2024)

Enhancing generalization in high energy physics using white-box adversarial attacks. - Franck Rothen; Samuel Klein; Matthew Leigh; Tobias Golling (CoRR, 2024)

Masked particle modeling on sets: towards self-supervised high energy physics foundation models. - Tobias Golling; Lukas Heinrich; Michael Kagan; Samuel Klein; Matthew Leigh; Margarita Osadchy; John Andrew Raine (Mach. Learn. Sci. Technol., 2024)