3 papers
cs.LG2026
Beyond a Better Score: Long-Horizon Agentic ML Development and Evaluation Protocol for Physics Time Series
Yue Ma, Lucas Venetoulias, Akbota Assan +1
Physics time-series data are central to fundamental discoveries involving dark matter, neutrinos, and gravitational waves. Machine learning has shown strong potential to recover we…
cs.LG2024
TIDMAD: Time Series Dataset for Discovering Dark Matter with AI Denoising
J. T. Fry, Xinyi Hope Fu, Zhenghao Fu +3
Dark matter makes up approximately 85% of total matter in our universe, yet it has never been directly observed in any laboratory on Earth. The origin of dark matter is one of the…
physics.data-an2023
Generative Models for Simulation of KamLAND-Zen
Z. Fu, C. Grant, D. M. Krawiec +2
The next generation of searches for neutrinoless double beta decay (0ν\b{eta}\b{eta}) are poised to answer deep questions on the nature of neutrinos and the source of the Universe'…