Search Results for author: Giuseppe Cerati

Found 7 papers, 2 papers with code

NuGraph2: A Graph Neural Network for Neutrino Physics Event Reconstruction

no code implementations18 Mar 2024 V Hewes, Adam Aurisano, Giuseppe Cerati, Jim Kowalkowski, Claire Lee, Wei-keng Liao, Daniel Grzenda, Kaushal Gumpula, Xiaohe Zhang

This article describes NuGraph2, a Graph Neural Network (GNN) for low-level reconstruction of simulated neutrino interactions in a LArTPC detector.

Graph Neural Network

Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs

no code implementations27 Jan 2021 Giuseppe Cerati, Peter Elmer, Brian Gravelle, Matti Kortelainen, Vyacheslav Krutelyov, Steven Lantz, Mario Masciovecchio, Kevin McDermott, Boyana Norris, Allison Reinsvold Hall, Micheal Reid, Daniel Riley, Matevž Tadel, Peter Wittich, Bei Wang, Frank Würthwein, Avraham Yagil

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks.

High Energy Physics - Experiment Distributed, Parallel, and Cluster Computing

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

no code implementations25 Mar 2020 Xiangyang Ju, Steven Farrell, Paolo Calafiura, Daniel Murnane, Prabhat, Lindsey Gray, Thomas Klijnsma, Kevin Pedro, Giuseppe Cerati, Jim Kowalkowski, Gabriel Perdue, Panagiotis Spentzouris, Nhan Tran, Jean-Roch Vlimant, Alexander Zlokapa, Joosep Pata, Maria Spiropulu, Sitong An, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy Usher

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision.

Instrumentation and Detectors High Energy Physics - Experiment Computational Physics Data Analysis, Statistics and Probability

Novel deep learning methods for track reconstruction

3 code implementations14 Oct 2018 Steven Farrell, Paolo Calafiura, Mayur Mudigonda, Prabhat, Dustin Anderson, Jean-Roch Vlimant, Stephan Zheng, Josh Bendavid, Maria Spiropulu, Giuseppe Cerati, Lindsey Gray, Jim Kowalkowski, Panagiotis Spentzouris, Aristeidis Tsaris

The second set of models use Graph Neural Networks (GNNs) for the tasks of hit classification and segment classification.

High Energy Physics - Experiment Data Analysis, Statistics and Probability

Cannot find the paper you are looking for? You can Submit a new open access paper.