3D Variable Scene Graphs for long-term semantic scene change prediction.

This is a repo for my Bertelsmann Data Science Scholarship Challenge: notes, exercises, quizzes.

Create light curves from UVIT data.

R package for delineating temporal dataset shifts in Eletronic Health Records

Efficient detection of planets transiting active stars

Library for Variability-Aware Differencing and the Analysis of Edits to Preprocessor-Based Software Product Lines

R code for the discovery of COVID-19 subgroups by symptoms and comorbidities.

R scripts for parsing and plotting the change in heart rate variability (HRV) statistics. They work with data exported from Elite HRV and Heart Rate Monitor.

A model-driven revision and variation control system for the Eclipse Modeling Framework

A collection of simple Python Programs for Applied Statistics.

Measuring and visualizing biomedical data variability/heterogeneity across data sources

GWAS of trait variance (C++)

A tool to visualize the variability of a DNA region

Code to add a mathematical model of voltage-clamp artefacts to your ion channel simulations

Example code that calculates the Hybrid Precipitation Index described in Chelton and Risien, 2020.

To describe age-gender unbiased COVID-19 subphenotypes regarding severity patterns through a two-stage clustering approach using patient phenotypes and demographic features. Additional source and temporal variability assessments are included as part of data quality analyses.

A hub that contains notebooks that perform elementary descriptive statistics of populations and samples and demonstrates 3 hypothesis tests- Welch t-test, Correlation, and Chi-square test. It shows how to run them in python and understand the results

OpenTOSCA Vintner is a TOSCA preprocessing and management layer which is able to deploy applications based on TOSCA orchestrator plugins. Preprocessing includes, e.g., the resolving of deployment variability.

This module is made to represent the variability of a model inside Modelio, and to allow the connection with an external variability management tool. The user shall design a 150% model for his system, and will be able to generate variants of it.

Code supporting paper: A forward modeling approach to AGN variability – method description and early applications (2019ApJ...883..139S)