8 citations · 17 across the 10 of their papers we have counts for
5 papers · 1 filter
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…
SuperSONIC: Cloud-Native Infrastructure for ML Inferencing
Dmitry Kondratyev, Benedikt Riedel, Yuan-Tang Chou +7
The increasing computational demand from growing data rates and complex machine learning (ML) algorithms in large-scale scientific experiments has driven the adoption of the Servic…
Entanglement and Bell Nonlocality in at the LHC using Machine Learning for Neutrino Reconstruction
Yulei Zhang, Bai-Hong Zhou, Qi-Bin Liu +5
Experiments at the CERN Large Hadron Collider (LHC) have accumulated an unprecedented amount of data corresponding to a large variety of quantum states. Although searching for new…
Building Machine Learning Challenges for Anomaly Detection in Science
Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova +148
Scientific discoveries are often made by finding a pattern or object that was not predicted by the known rules of science. Oftentimes, these anomalous events or objects that do not…
Track reconstruction as a service for collider physics
Haoran Zhao, Yuan-Tang Chou, Yao Yao +11
Optimizing charged-particle track reconstruction algorithms is crucial for efficient event reconstruction in Large Hadron Collider (LHC) experiments due to their significant comput…