John Andrew Raine

18 papers Journal 18

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals. Frontiers Big Data John Andrew Raine, Samuel Klein, Debajyoti Sengupta, Tobias Golling
2024	J	`jnl`	Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models. CoRR Lukas Heinrich, Tobias Golling, Michael Kagan, Samuel Klein, Matthew Leigh, Margarita Osadchy, John Andrew Raine
2024	J	`jnl`	Masked particle modeling on sets: towards self-supervised high energy physics foundation models. Mach. Learn. Sci. Technol. Tobias Golling, Lukas Heinrich, Michael Kagan, Samuel Klein, Matthew Leigh, Margarita Osadchy, John Andrew Raine
2024	J	`jnl`	PIPPIN: Generating variable length full events from partons. CoRR Guillaume Quétant, John Andrew Raine, Matthew Leigh, Debajyoti Sengupta, Tobias Golling
2024	J	`jnl`	Variational inference for pile-up removal at hadron colliders with diffusion models. CoRR Malte Algren, Chris Pollard, John Andrew Raine, Tobias Golling
2023	J	`jnl`	CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation. CoRR Debajyoti Sengupta, Samuel Klein, John Andrew Raine, Tobias Golling
2023	J	`jnl`	Decorrelation using Optimal Transport. CoRR Malte Algren, John Andrew Raine, Tobias Golling
2023	J	`jnl`	EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion. CoRR Erik Buhmann, Cedric Ewen, Darius A. Faroughy, Tobias Golling, Gregor Kasieczka, Matthew Leigh, Guillaume Quétant, John Andrew Raine, Debajyoti Sengupta, David Shih
2023	J	`jnl`	Flow Away your Differences: Conditional Normalizing Flows as an Improvement to Reweighting. CoRR Malte Algren, Tobias Golling, Manuel Guth, Chris Pollard, John Andrew Raine
2023	J	`jnl`	Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation. CoRR Tobias Golling, Samuel Klein, Radha Mastandrea, Benjamin Nachman, John Andrew Raine
2023	J	`jnl`	Improving new physics searches with diffusion models for event observables and jet constituents. CoRR Debajyoti Sengupta, Matthew Leigh, John Andrew Raine, Samuel Klein, Tobias Golling
2023	J	`jnl`	PC-Droid: Faster diffusion and improved quality for particle cloud generation. CoRR Matthew Leigh, Debajyoti Sengupta, John Andrew Raine, Guillaume Quétant, Tobias Golling
2023	J	`jnl`	PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics. CoRR Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling
2023	J	`jnl`	SuperCalo: Calorimeter shower super-resolution. CoRR Ian Pang, John Andrew Raine, David Shih
2023	J	`jnl`	Topological Reconstruction of Particle Physics Processes using Graph Neural Networks. CoRR Lukas Ehrke, John Andrew Raine, Knut Zoch, Manuel Guth, Tobias Golling
2023	J	`jnl`	ν CoRR John Andrew Raine, Matthew Leigh, Knut Zoch, Tobias Golling
2022	J	`jnl`	Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation. CoRR Samuel Klein, John Andrew Raine, Tobias Golling
2022	J	`jnl`	ν-Flows: Conditional Neutrino Regression. CoRR Matthew Leigh, John Andrew Raine, Knut Zoch, Tobias Golling