41 citations · 48 across the 6 of their papers we have counts for
6 papers
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
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…
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…
Joint searches by FACT, H.E.S.S., MAGIC and VERITAS for VHE gamma-ray emission associated with neutrinos detected by IceCube
Fabian Schüssler, Halim Ashkar, Elisa Bernardini +11
The sources of the astrophysical flux of high-energy neutrinos detected by IceCube are still largely unknown, but searches for temporal and spatial correlation between neutrinos an…
tilepy: rapid tiling strategies in mid/small FoV observatories
Fabian Schüssler, Halim Ashkar, Mathieu de Bony de Lavergne +1
The challenges inherent to time-domain multi-messenger astronomy require strategic actions so that adapted, optimized follow-up observations are performed efficiently. In particula…
Search for Quantum Gravity Using Astrophysical Neutrino Flavour with IceCube
R. Abbasi, M. Ackermann, J. Adams +378
Along their long propagation from production to detection, neutrino states undergo quantum interference which converts their types, or flavours. High-energy astrophysical neutrinos…