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Found 7 papers, 5 papers with code
Shared Data and Algorithms for Deep Learning in Fundamental Physics
We introduce a Python package that provides simply and unified access to a collection of datasets from fundamental physics research - including particle physics, astroparticle physics, and hadron- and nuclear physics - for supervised machine learning studies.
Lorentz Boost Networks: Autonomous Physics-Inspired Feature Engineering
The LBN also enables the formation of further composite particles, which are then transformed into said rest frames by Lorentz transformation.
High Energy Physics - Experiment High Energy Physics - Phenomenology
Machine Learning in High Energy Physics Community White Paper
In this document we discuss promising future research and development areas for machine learning in particle physics.
BIG-bench Machine Learning
Vocal Bursts Intensity Prediction
Precise simulation of electromagnetic calorimeter showers using a Wasserstein Generative Adversarial Network
The generator is constraint during the training such that the generated showers show the expected dependency on the initial energy and the impact position.
Instrumentation and Detectors
Generating and refining particle detector simulations using the Wasserstein distance in adversarial networks
We use adversarial network architectures together with the Wasserstein distance to generate or refine simulated detector data.
Instrumentation and Methods for Astrophysics High Energy Physics - Experiment
CRPropa 3 - a Public Astrophysical Simulation Framework for Propagating Extraterrestrial Ultra-High Energy Particles
We present the simulation framework CRPropa version 3 designed for efficient development of astrophysical predictions for ultra-high energy particles.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies High Energy Astrophysical Phenomena
PARSEC: A Parametrized Simulation Engine for Ultra-High Energy Cosmic Ray Protons
We present a new simulation engine for fast generation of ultra-high energy cosmic ray data based on parametrizations of common assumptions of UHECR origin and propagation.
High Energy Astrophysical Phenomena
