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Logo for JuPedSim

JuPedSim

JuPedSim is a framework designed to support students and researchers in investigating pedestrian dynamics and conducting research related to the development and validation of new models or model features. It enables the analysis of experiments and facilitates the proper visualization of results.

  • Information
  • Modeling
  • open source
  • + 3
  • Python
  • C++
  • Jupyter Notebook
  • + 3
4
7
Logo for O3as

O3as

The O3as service provides tools to extract essential information on ozone trends from large climate prediction model data and allows the production of scientifically valuable figures coherently.

  • Earth & Environment
  • Ozone recovery
  • Stratospheric ozone
    9
    7
    Logo for pkgndep

    pkgndep

    A new metric named 'dependency heaviness' is proposed that measures the number of additional dependency packages that a parent package brings to its child package and are unique to the dependency packages imported by all other parents.

    • Data analysis
    • Data Visualization
    • FAIR Data
    • + 3
    • R
    • HTML
    • JavaScript
    • + 1
    1
    7
    Logo for t8code

    t8code

    t8code (spoken as "tetcode") is a C/C++ library to manage parallel adaptive meshes with various element types. t8code uses a collection (a forest) of multiple connected adaptive space-trees in parallel and scales to at least one million MPI ranks and over 1 trillion mesh elements.

    • data managment
    • Data Visualization
    • exascale
    • + 3
    • C++
    • C
    • CMake
    • + 3
    17
    7
    Logo for hCoCena - horizontal integration and analysis of transcriptomics datasets

    hCoCena - horizontal integration and analysis of transcriptomics datasets

    hCoCena is an R-package that allows you to comprehensively and easily analyse your transcriptomics data. It also provides the option to integrate several datasets using a network-based integration approach and analyse them jointly. Tutorials and a Docker image exist to help you get to know the tool.

    • Data analysis
    • Gene Expression
    • Health
    • + 1
    • R
    5
    6
    Logo for KaMPIng - Karlsruhe MPI next generation

    KaMPIng - Karlsruhe MPI next generation

    KaMPIng is a flexible and (near) zero-overhead C++ wrapper for MPI, covering the whole range of abstraction levels from low-level MPI calls to convenient STL-style bindings. This allows for both rapid prototyping and highly engineered distributed algorithms.

    • C++
    • High performance computing
    • MPI
    • + 1
    • C++
    • CMake
    • Shell
    • + 1
    8
    6
    Logo for LUCYD

    LUCYD

    LUCYD - A Feature-Driven Richardson-Lucy Deconvolution Network

    • deblurring
    • deconvolution
    • image enhancement
    • + 1
    • Python
    0
    6
    Logo for Minterpy

    Minterpy

    Minterpy is an open-source Python package for multivariate polynomial interpolation as well as related tasks, like nonlinear polynomial regression, numerical integration, global optimization, level-set methods, and much more.

    • Interpolation
    • Modeling
    • numerical Integration
    • Python
    6
    6
    Logo for mmpxrt

    mmpxrt

    Raytracing code for x-ray spectrometers with (not only) mossaic crystals Helps with design and analysis of x-ray spectrometers. Useful tool for (rather) experienced physicist.

    • Python
    • CSS
    • HTML
    • + 2
    1
    6
    Logo for nnDetection

    nnDetection

    nnDetection: A Self-configuring Method for Medical Object Detection

    • 3d-object-detection
    • biomedical image analysis
    • Detection
    • + 3
    • Python
    • Cuda
    • Dockerfile
    • + 3
    0
    6
    Logo for PtyLab.m/py/jl

    PtyLab.m/py/jl

    A cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography

    • computational physics
    • Data analysis
    • Data Visualization
    • + 10
    • Jupyter Notebook
    • Python
    14
    6
    Logo for BioAutoML - Democratizing Machine Learning in Life Sciences

    BioAutoML - Democratizing Machine Learning in Life Sciences

    BioAutoML automatically runs an end-to-end ML pipeline that can be effectively employed by non-experts. BioAutoML does not require specialized human assistance, i.e., it only needs a training dataset of biological sequences (FASTA files) to perform an end-to-end ML experiment.

    • Artificial Intelligence
    • Big data
    • BioAutoML
    • + 3
    • Jupyter Notebook
    • Python
    7
    5