John Andrew Raine

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 16

Top Topics

Maximum Likelihood Estimation

Multivariate Gaussian

Diffusion Models

Top Venues

Frontiers Big Data

Publications

Lukas Heinrich, Tobias Golling, Michael Kagan, Samuel Klein, Matthew Leigh, Margarita Osadchy, John Andrew Raine
Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models. CoRR (2024)
Guillaume Quétant, John Andrew Raine, Matthew Leigh, Debajyoti Sengupta, Tobias Golling
PIPPIN: Generating variable length full events from partons. CoRR (2024)
John Andrew Raine, Samuel Klein, Debajyoti Sengupta, Tobias Golling
CURTAINs for your sliding window: Constructing unobserved regions by transforming adjacent intervals. Frontiers Big Data 6 (2024)
Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, Tobias Golling
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics. CoRR (2023)
John Andrew Raine, Matthew Leigh, Knut Zoch, Tobias Golling
-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows. CoRR (2023)
Erik Buhmann, Cedric Ewen, Darius A. Faroughy, Tobias Golling, Gregor Kasieczka, Matthew Leigh, Guillaume Quétant, John Andrew Raine, Debajyoti Sengupta, David Shih
EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion. CoRR (2023)
Lukas Ehrke, John Andrew Raine, Knut Zoch, Manuel Guth, Tobias Golling
Topological Reconstruction of Particle Physics Processes using Graph Neural Networks. CoRR (2023)
Tobias Golling, Samuel Klein, Radha Mastandrea, Benjamin Nachman, John Andrew Raine
Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation. CoRR (2023)
Debajyoti Sengupta, Matthew Leigh, John Andrew Raine, Samuel Klein, Tobias Golling
Improving new physics searches with diffusion models for event observables and jet constituents. CoRR (2023)
Ian Pang, John Andrew Raine, David Shih
SuperCalo: Calorimeter shower super-resolution. CoRR (2023)
Malte Algren, Tobias Golling, Manuel Guth, Chris Pollard, John Andrew Raine
Flow Away your Differences: Conditional Normalizing Flows as an Improvement to Reweighting. CoRR (2023)
Matthew Leigh, Debajyoti Sengupta, John Andrew Raine, Guillaume Quétant, Tobias Golling
PC-Droid: Faster diffusion and improved quality for particle cloud generation. CoRR (2023)
Malte Algren, John Andrew Raine, Tobias Golling
Decorrelation using Optimal Transport. CoRR (2023)
Debajyoti Sengupta, Samuel Klein, John Andrew Raine, Tobias Golling
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation. CoRR (2023)
Matthew Leigh, John Andrew Raine, Knut Zoch, Tobias Golling
ν-Flows: Conditional Neutrino Regression. CoRR (2022)
Samuel Klein, John Andrew Raine, Tobias Golling
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation. CoRR (2022)