model-calibration

A Library for Uncertainty Quantification.

RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.

[ICCV 2021 Oral] Deep Evidential Action Recognition

a modeling environment tailored to parameter estimation in dynamical systems

Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.

A phenology modelling framework in R

[MICCAI2022] Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores.

pycalibrate is a Python library to visually analyze model calibration in Jupyter Notebooks

Parameter estimation and model calibration using Genetic Algorithm optimization in Python.

Official code for "On Calibrating Diffusion Probabilistic Models"

System Dynamics Review (2021)

Simulating and Optimising Dynamical Models in Python 3

An efficient Java™ solver implementation for SBML

Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published in NeurIPS 2022.

An overview about PROFOUND code, data, protocols and algorithms for interfacing, calibrating and comparing forest models

Calibration of the monodomain model coupled with the Rogers-McCulloch model for the ionic current: design of a protocol for impulse delivery from an ATP device.

GEARS a toolbox for Global parameter Estimation with Automated Regularisation via Sampling by Jake Alan Pitt and Julio R. Banga

Calibration of a wind erosion model using remote sensing-derived vegetation characteristics

ARBO is a package for simulation and analysis of arbovirus nonlinear dynamics.

A collection of time-efficient state estimation algorithms for the medium-fidelity WindFarmSimulator (WFSim) control model