Pyhep 2021 A Python Package Pyhep 2021 A Python Package

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This talk will cover the the best practices of making a highly compatible and installable The declarative approach to data analysis provides high-level abstractions for users to operate on their datasets in a much more ... Matthew Feickert gives a tutorial on using pyhf for accelerating analyses and preserving likelihoods. Part of the The BumpHunter algorithm is a well known test statistic designed to find a excess (or a deficit) in a data histogram with respect to ... In high energy physics, the standard convention for expressing physical quantities is natural units. The standard paradigm sets c ... Henry Schreiner gives a tutorial for High Performance

The KM3NeT collaboration builds, operates and maintains two water Cherenkov detectors for neutrino astronomy and physics ... CERN's Open Data Portal has 1000's of datasets, in many formats. The ServiceX project reads experiment data files of various ... Over the last decades noble liquid time projection chambers (TPCs) have become one of the forefront technologies for the search ... Expanding HEP datasets and analysis challenges continues to give rise to advancing software within the ecosystem. The LHCb ...

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2021 How to Install a Package in Python | Beginner Python Tutorial
PyHEP 2021: Julia in HEP & Python Open Discussion
PyHEP 2020 pyhf Tutorial
PyHEP 2021: MadMiner: a python based tool for simulation-based inference in HEP
PyHEP 2021: pyBumpHunter : A model agnostic bump hunting tool in python
PyHEP 2021: NatPy, a simple Python module for dealing with and converting natural units
PyHEP 2020 High Performance Python
PyHEP 2021: Python-based tools and frameworks for KM3NeT
PyHEP 2021: Monday 5th July
PyHEP 2021: Level-up your Python (Part II)
PyHEP 2021: Using Python, coffea, and ServiceX to Rediscover the Higgs. Twice.
PyHEP 2020 C and C++ Python Bindings

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Last Updated: June 24, 2026

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