A Library for Uncertainty Quantification.
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Updated
Jul 9, 2024 - Python
A Library for Uncertainty Quantification.
[ICCV 2021 Oral] Deep Evidential Action Recognition
Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
[CVPR 2023] Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection
Official code for "On Calibrating Diffusion Probabilistic Models"
Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published at NeurIPS 2022.
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".
Simulating and Optimising Dynamical Models in Python 3
Parameter estimation and model calibration using Genetic Algorithm optimization in Python.
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.
Calibration of the significant Social Force Parameters in Vissim
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