UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
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Updated
Feb 6, 2025 - Python
Error (or uncertainty) propagation is the practice of analyzing and accounting for the effect of numeric quantities' uncertainties on the results of functions that involve them.
When variables used in a function or mathematical operation have errors (due to measurement uncertainties, random fluctuations, sample variance, etc.), error propagation can be used to determine the resulting error of the function's output.
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
Multi-Object Tracking with Uncertain Detections [ECCV 2024 UnCV]
Sampling nuclear data and uncertainty
Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure
Python library for dealing with uncertainties and upper/lower limits
Uncertainties in topographic metrics due to truncation errors and elevation uncertainty
Uncertainty-Aware CNN - Uncertainty propagation in CNN
Global sensitivity analysis that takes into account correlations and dependencies in the LCA model during uncertainty propagation with Monte Carlo approach.
A generalised soft-clustering algorithm for propagating difficult-to-quantify effects into fuzzy clusters.
Uncertainty propagation and global sensitivity analysis for computational economic models
Experiments with incorporating uncertainty information in back prop. algorithm
A short and sweet library handling uncertainty in calculations. Can use both standard, probabilistic uncertainties and maximal uncertainties for arbitrary functions over arbitrary variables.
A Measurement Calculator with Fixed Point Precision, Uncertainties, and Units.
This code performs generalized Brownian dynamics (GBD) simulations of a microparticle embedded in a viscoelastic fluid and calculates and propagates statistical and other sources of error in passive microrheology
Global sensitivity analysis that takes into account correlations and dependencies in the LCA model during uncertainty propagation with Monte Carlo approach.
Uncertainty Quantification in Large Dynamical Systems
Allows to deal with power series which coefficients contain uncertainties
A lightweight Python utility providing values with associated uncertainty
Contains a method in Python to compute the uncertainty of an inventory (such as a pollutant inventory or a greenhouse gas inventory), based on input uncertainty for specific sub-categories of this inventory.