5 papers
RODEM Jet Datasets
Knut Zoch, John Andrew Raine, Debajyoti Sengupta +1
We present the RODEM Jet Datasets, a comprehensive collection of simulated large-radius jets designed to support the development and evaluation of machine-learning algorithms in pa…
PIPPIN: Generating variable length full events from partons
Guillaume Quétant, John Andrew Raine, Matthew Leigh +2
This paper presents a novel approach for directly generating full events at detector-level from parton-level information, leveraging cutting-edge machine learning techniques. To ad…
SkyCURTAINs: Model agnostic search for Stellar Streams with Gaia data
Debajyoti Sengupta, Stephen Mulligan, David Shih +2
We present SkyCURTAINs, a data driven and model agnostic method to search for stellar streams in the Milky Way galaxy using data from the Gaia telescope. SkyCURTAINs is a weakly su…
Calorimeter shower superresolution
Ian Pang, John Andrew Raine, David Shih
Calorimeter shower simulation is a major bottleneck in the Large Hadron Collider computational pipeline. There have been recent efforts to employ deep-generative surrogate models t…
Complete Optimal Non-Resonant Anomaly Detection
Gregor Kasieczka, John Andrew Raine, David Shih +1
We propose the first-ever complete, model-agnostic search strategy based on the optimal anomaly score, for new physics on the tails of distributions. Signal sensitivity is achieved…