4 papers
hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware
Jan-Frederik Schulte, Benjamin Ramhorst, Chang Sun +50
We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can b…
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…
A Neural Network-Based Search for Unmodeled Transients in LIGO-Virgo-KAGRA's Third Observing Run
Ryan Raikman, Eric A. Moreno, Katya Govorkova +13
This paper presents the results of a Neural Network (NN)-based search for short-duration gravitational-wave transients in data from the third observing run of LIGO, Virgo, and KAGR…
SymbolFit: Automatic Parametric Modeling with Symbolic Regression
Ho Fung Tsoi, Dylan Rankin, Cecile Caillol +6
We introduce SymbolFit, a framework that automates parametric modeling by using symbolic regression to perform a machine-search for functions that fit the data while simultaneously…