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

[CVPR 2023] Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection

Official code for "On Calibrating Diffusion Probabilistic Models"

Delta hedging under SABR model

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

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

A toolbox for the calibration and evaluation of simulation models.

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

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

Simulating and Optimising Dynamical Models in Python 3

This is the official PyTorch codebase for the ACL 2023 paper: "What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization".

System Dynamics Review (2021)

ARBO is a Matlab/C++ package for simulation and analysis of arbovirus nonlinear dynamics.

An R package to produce standard graphs for HEC-RAS models.

An efficient Java™ solver implementation for SBML