ISciNumPy.dev
  • Links
    • Useful Links
    • Software
    • Writing
    • Presentations
    • Illustrations and videos
    • My UC site
  • Site
    • Archives
    • Tags
    • Categories
  • About
    • About me
    • My projects
ISciNumPy.dev

Presentations


S&C Round Table

CMake: Best Practices

Feb 2, 2021
Virtual

    PyHEP 2020

    The boost-histogram Package

    Jul 17, 2020
    Virtual

      SciPy 2020

      boost-histogram: High-performance histograms as objects

      Jul 7, 2020
      Virtual

      • DOI 10.25080/Majora-342d178e-009

      Princeton Research Data Management Workshop 2020

      Python, NumPy, and Pandas

      Jan 28, 2020
      Princeton University

      • GitHub repo
      Mybinder badge

      Princeton Research Computing Fall Mini-courses and Workshops

      High-Performance Python: GPUs

      Dec 5, 2019
      Princeton, NJ, USA

        Princeton Research Computing Fall Mini-courses and Workshops

        High-Performance Python: CPUs

        Nov 20, 2019
        Princeton, NJ, USA

          Mybinder badge

          CHEP 2019

          Recent developments in histogram libraries

          Nov 7, 2019
          Adelaide, South Australia

          • Video

          PyHEP 2019

          Python 3.8: What's new

          Oct 17, 2019
          Abingdon, UK

            • ««
            • «
            • 3
            • 4
            • 5
            • 6
            • 7
            • »
            • »»
            Posts
            • Tools plenary: cibuildwheel
            • Tools plenary: scikit-build
            • AI tools in OSS development
            • Tools that help you write better code
            • Tools to help you write better code
            • What's new in Python π
            • Python Histograms
            • Using Venvs
            • Packaging a Scientific Python Project
            • Building Python Packages
            • Tools to help you write better code
            • The two flavors of Python 3.13
            • Modern binary build systems
            • Software Quality Assurance Tooling
            • Learning Rust with Advent of Code 2023
            • Project report - henryiii
            • Software Quality Assurance Tooling
            • Software Quality Assurance Tooling
            • What's new in Python 3.11
            • Everything you didn't know you needed
            • Building binary extensions with pybind11, scikit build, and cibuildwheel
            • Awkward Packaging: building Scikit-HEP
            • Scikit-HEP Developer Pages: Guidelines for modern packaging
            • Building Binary Packages
            • Digital RSE: Automatic Code Quality Checks
            • boost-histogram / Hist
            • CMake best practices
            • pybind11
            • Powerful Python Packaging for Scientific Codes
            • High-Performance Histogramming for HEP Analysis
            • Level Up Your Python (part 2)
            • Level Up Your Python (part 1)
            • CMake: Best Practices
            • The boost-histogram Package
            • boost-histogram: High-performance histograms as objects
            • Python, NumPy, and Pandas
            • High-Performance Python: GPUs
            • High-Performance Python: CPUs
            • Recent developments in histogram libraries
            • Python 3.8: What's new
            • Python Histogramming Packages
            • Boost Histogram Roadmap
            • Modern CMake Workshop
            • Modern CMake
            • AmpGen & Particle/DecayLanguage
            • Histograms
            • A hybrid deep learning approach to vertexing
            • boost-histogram and hist
            • A hybrid deep learning approach to vertexing
            • Conda: a complete reproducible ROOT environment in under 5 minutes
            • Machine Learning for the Primary Vertex reconstruction
            • A hybrid deep learning approach to vertexing
            • PV finding with CNNs
            • iminuit: interactive python wrapper around MINUIT2
            • A Python upgrade to the GooFit package for parallel fitting
            • Tools to bind to Python
            • Goofit 2.0
            • Recent developments in GooFit
            • GPUs in LHCb for Analysis
            • Modernizing GooFit: A Case Study
            • CLI11

            Henry Schreiner  •  © 2026  •  ISciNumPy.dev

            Hugo v0.161.1 powered  •  Theme Beautiful Hugo adapted from Beautiful Jekyll  • [1abc9222]