1 citations · 1 across the 3 of their papers we have counts for
4 papers
Edge Machine Learning for Cluster Counting in Next-Generation Drift Chambers
Deniz Yilmaz, Liangyu Wu, Julia Gonski +2
Drift chambers have long been central to collider tracking, but future machines like a Higgs factory motivate higher granularity and cluster counting for particle ID, posing new da…
Convolutional Autoencoders for Data Compression and Anomaly Detection in Small Satellite Technologies
Dishanand Jayeprokash, Julia Gonski
Small satellite technologies have enhanced the potential and feasibility of geodesic missions, through simplification of design and decreased costs allowing for more frequent launc…
Analysis of Hardware Synthesis Strategies for Machine Learning in Collider Trigger and Data Acquisition
Haoyi Jia, Abhilasha Dave, Julia Gonski +1
To fully exploit the physics potential of current and future high energy particle colliders, machine learning (ML) can be implemented in detector electronics for intelligent data p…
Highlights from Long-Lived Particle Searches at ATLAS
Julia Gonski
The latest results of long-lived particle (LLP) searches from the ATLAS Experiment at the Large Hadron Collider are presented. Analyses are presented with a focus on detector subsy…