Geant4 toolkit for the simulation of the passage of particles through matter - NIM A 506 (2003) 250-303

pure-Python HistFactory implementation with tensors and autodiff

Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.

Machine Learning for High Energy Physics.

Metapackage of Scikit-HEP project data analysis packages for Particle Physics.

Package to deal with particles, the PDG particle data table, PDGIDs, etc.

Native Julia I/O package to work with CERN ROOT files objects (TTree and RNTuple)

A Deep learning library for neutrino telescopes

Header only framework for data analysis in massively parallel platforms.

Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation

Celeritas is a new Monte Carlo transport code designed to accelerate scientific discovery in high energy physics by improving detector simulation throughput and energy efficiency using GPUs.

A Python package for flavour physics phenomenology in the Standard model and beyond

Automatic parametric modeling with symbolic regression

Standalone monitor for process resource consumption

Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics

Quantum Transformers for High Energy Physics Analysis at the Large Hadron Collider

Academic style Slidev theme for High Energy Physics

Legacy Repository - Superseded by https://github.com/fermi-lat/ScienceTools

Package to parse decay files, describe and convert particle decays between digital representations.

ATLAS Run 2 and Run 3 analysis framework for AnalysisTop and AnalysisBase for proton-smashing physics