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22 search results found

Bayesian Neural Networks ⭐ 1,633

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Conformal Prediction ⭐ 349

Lightweight, useful implementation of conformal prediction on real data.

Conformal_classification ⭐ 159

Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

Uncertaintynn ⭐ 85

Implementation and evaluation of different approaches to get uncertainty in neural networks

Conformal Time Series ⭐ 60

Conformal prediction for time-series applications.

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

Bioindustrial Park ⭐ 33

BioSTEAM's Premier Repository for Biorefinery Models and Results

Bayescap ⭐ 32

(ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

Mtl Homoscedastic Uncertainty ⭐ 31

Multi Task Learning Implementation with Homoscedastic Uncertainty in Tensorflow

Metrolopy ⭐ 22

Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure

A library for uncertainty quantification based on PyTorch

Temporal Smoothing ⭐ 16

(AAAI 2021) Official TensorFlow implementation of "Vector Quantized Bayesian Neural Network Inference for Data Streams", a temporal smoothing for efficient uncertainty estimation

Vars Tool ⭐ 8

VARS-TOOL sensitivity analysis package in Python

WIP implementation of Probabilistic Differential Dynamic Programming in PyTorch

A numerical framework to estimate hardware, data processing and pointing uncertainties of ground-based Doppler wind lidars

Supplementary material to reproduce "Multivariate Deep Evidential Regression"

Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians

Unreasonable_effective_der ⭐ 7

Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"

Input data and source code for the paper "Modelling uncertainty in coupled electricity and gas system models—is it worth the effort?"

Gaussiandenoisingposterior ⭐ 6

We derive a fundamental property of the posterior distribution in Gaussian denoising, and use it to propose a new way for uncertainty visualization, which requires no training or fine-tuning.

Arch_uncert ⭐ 6

Code for "Variational Depth Search in ResNets" (https://arxiv.org/abs/2002.02797)

Plotting Uncertainty Ellipses ⭐ 5

This Jupyter notebook demonstrates how to properly plot uncertainty (confidence) ellipses for 2D normally distributed data.

Tutorial materials for Social Simulation Fest 2021

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