Publications

Influencer Loss: End-to-end Geometric Representation Learning for Track Reconstruction

Apr 23, 2024

Hierarchical Graph Neural Network

Apr 23, 2024

Graph neural networks for particle reconstruction in high energy physics detectors (2020)

Apr 23, 2024

Software and computing for Run 3 of the ATLAS experiment at the LHC

Jan 1, 2024

Graph Neural Networks for track reconstruction in the ATLAS ITk detector at the Large Hadon Collider

Jan 1, 2024

A Language Model for Particle Tracking

Jan 1, 2024

Semi-equivariant GNN architectures for jet tagging

Jan 1, 2023

Reconstruction of Large Radius Tracks with the Exa. TrkX pipeline

Jan 1, 2023

Physics Performance of the ATLAS GNN4ITk Track Reconstruction Chain

Jan 1, 2023

Physics Performance of the ATLAS GNN4ITk Track Reconstruction Chain

Jan 1, 2023

Hierarchical Graph Neural Networks for Particle Track Reconstruction

Jan 1, 2023

Heterogeneous graph neural network for identifying hadronically decayed tau leptons at the high luminosity LHC

Jan 1, 2023

Graph structure from point clouds: Geometric attention is all you need

Jan 1, 2023

Graph Neural Networks for Radiological/Nuclear Detection with Static Detector Networks

Jan 1, 2023

Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers

Jan 1, 2023

Equivariant graph neural networks for charged particle tracking

Jan 1, 2023

Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks

Jan 1, 2023

Deep Learning for Tritium Detection Using Scientific CCDs

Jan 1, 2023

Accelerating the inference of the Exa. TrkX pipeline

Jan 1, 2023

Theory of Collider Phenomena

Jan 1, 2022

Symmetry group equivariant architectures for physics

Jan 1, 2022

SISSA: Applying and optimizing the Exa. TrkX Pipeline on the OpenDataDetector with ACTS

Jan 1, 2022

Graph neural networks in particle physics: Implementations, innovations, and challenges

Jan 1, 2022

Graph Neural Network Track Reconstruction for the ATLAS ITk Detector

Jan 1, 2022

Benchmarking GPU and TPU Performance with Graph Neural Networks

Jan 1, 2022

ATLAS ITk Track Reconstruction with a GNN-based pipeline

Jan 1, 2022

arXiv: TF07 Snowmass Report: Theory of Collider Phenomena

Jan 1, 2022

arXiv: Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning

Jan 1, 2022

Performance of a geometric deep learning pipeline for HL-LHC particle tracking

Jan 1, 2021

Graph neural network for object reconstruction in liquid argon time projection chambers

Jan 1, 2021

Developing Lorentz Equivariant Graph Neural Networks for Top Quark Tagging

Jan 1, 2021

Convergent Bayesian global fits of 4D composite Higgs models

Jan 1, 2021

Track seeding and labelling with embedded-space graph neural networks

Jan 1, 2020

Minimal 4D Composite Higgs Models Under Current LHC Constraints

Jan 1, 2020

Graph neural networks for particle reconstruction in high energy physics detectors

Jan 1, 2020

arXiv: Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

Jan 1, 2020

The landscape of composite Higgs models

Jan 1, 2019

Exploring fine-tuning of the next-to-minimal composite Higgs model

Jan 1, 2019

Fine Tuning in Composite Higgs Models. pptx

Jan 1, 2017

Constraining fine tuning in Composite Higgs Models with partially composite leptons

Jan 1, 2017

ColliderBit: a GAMBIT module for the calculation of high-energy collider observables and likelihoods

Jan 1, 2017

WHAT’S THE MATTER? Supersymmetric Dark Matter Searches with CMS Data

Jan 1, 2014