uncertainty-quantification

There are 26 repositories under uncertainty-quantification topic.

valeman / awesome-conformal-prediction
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
conformal-prediction python r machinelearning datascience deeplearning awesome awesome-list probability uncertainty-quantification uncertainty uncertainty-estimation probability-distribution probability-distributions machine-learning
3429
uncertainty-toolbox
uncertainty-toolbox / uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
uncertainty uncertainty-quantification uncertainty-estimation uncertainty-metrics calibration sharpness uncertainty-toolbox metrics visualizations visualization recalibration predictive-uncertainty scoring-rules uncertainty-calibration toolbox bayesian-neural-networks bayesian-deep-learning
Language:Python 1724
fortuna
awslabs / fortuna
A Library for Uncertainty Quantification.
ai bayesian-inference calibration conformal-prediction deep-learning flax jax machine-learning ml model-calibration neural-networks uncertainty uncertainty-calibration uncertainty-estimation uncertainty-quantification
Language:Python 855
SALib / SALib
Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and other methods.
sensitivity-analysis-library sensitivity-analysis sobol morris python global-sensitivity-analysis numpy salib joss uncertainty uncertainty-quantification
Language:Python 830
aangelopoulos / conformal-prediction
Lightweight, useful implementation of conformal prediction on real data.
computer-vision conformal conformal-inference conformal-prediction distribution-shift natural-language-processing time-series time-series-prediction uncertainty uncertainty-estimation uncertainty-quantification
Language:Jupyter Notebook 653
AlaaLab / deep-learning-uncertainty
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
deep-learning deep-neural-networks prediction-uncertainty uncertainty-estimation uncertainty-quantification
Language:Jupyter Notebook 581
EmuKit / emukit
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.
machine-learning bayesian-optimization uncertainty-quantification multi-fidelity experimental-design bayesian-quadrature sensitivity-analysis decision-making emulation python
Language:Python 566
jxzhangjhu / Awesome-LLM-Uncertainty-Reliability-Robustness
Awesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
awesome-list calibration chain-of-thought chatgpt gpt-3 gpt-4 hallucination in-context-learning large-language-models llms prompt-engineering prompting reliability robustness safety uncertainty-estimation uncertainty-quantification
517
IntelLabs / bayesian-torch
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
bayesian-deep-learning bayesian-inference bayesian-layers bayesian-neural-networks deep-learning deep-neural-networks pytorch stochastic-variational-inference uncertainty-estimation uncertainty-neural-networks uncertainty-quantification
Language:Python 457
chaospy
jonathf / chaospy
Chaospy - Toolbox for performing uncertainty quantification.
gaussian-quadrature sensitivity-analysis sparse-grids uncertainty-quantification variance-reduction
Language:Python 430
ENSTA-U2IS-AI / awesome-uncertainty-deeplearning
This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
awesome awesome-resources deep-learning deep-learning-tutorials deep-neural-networks machine-learning uncertainty-analysis uncertainty-estimation uncertainty-neural-networks uncertainty-quantification
396
henrikbostrom / crepes
Conformal classifiers, regressors and predictive systems
machine-learning conformal-prediction conformal-regressors conformal-predictive-systems python jupyter-notebook confidence-intervals cumulative-distribution-function regression sklearn prediction-intervals uncertainty-quantification quantile-regression conformal-classifiers scikit-learn prediction-sets
Language:Python 347
deephyper / deephyper
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
hyperparameter-search automl scalability neural-architecture-search deep-neural-networks hyperparameter-optimization autodl python ml tensorflow keras deep-learning hpc machine-learning multi-fidelity pytorch uncertainty-quantification
Language:Python 262
stefanradev93 / BayesFlow
A Python library for amortized Bayesian workflows using generative neural networks.
amortized-inference bayesian-inference deep-learning invertible-networks likelihood-free model-comparison parameter-estimation simulation-based uncertainty-quantification
Language:Python 254
SURGroup / UQpy
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
uncertainty-quantification uncertainty-propagation uncertainty-sampling probability probabilistic stochastic stochastic-process monte-carlo monte-carlo-simulation latin-hypercube latin-hypercube-sampling
Language:Python 253
IBM / UQ360
Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.
artificial-intelligence bayesianneuralnetwork calibration machine-learning metrics trusted-ai uncertainty uncertainty-estimates uncertainty-quantification
Language:Python 251
deel-ai / puncc
👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.
conformal-prediction uncertainty-estimation uncertainty-quantification conformal-inference conformal-regressors
Language:Python 243
openturns / openturns
Uncertainty treatment library
data-analysis metamodel optimization probability-distribution python reliability sensitivity stochastic-process uncertainty-quantification
Language:C++ 216
simetenn / uncertainpy
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
uncertainty-quantification sensitivity-analysis neuroscience python computational-modeling
Language:Python 212
aangelopoulos / conformal_classification
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).
prediction-sets conformal-prediction conformal machine-learning distribution-free nonparametric nonparametric-statistics classification imagenet artificial-intelligence neural-networks pytorch deep-neural-networks statistics computer-vision vision classifier uncertainty uncertainty-quantification
Language:Jupyter Notebook 211
idaholab / raven
RAVEN is a flexible and multi-purpose probabilistic risk analysis, validation and uncertainty quantification, parameter optimization, model reduction and data knowledge-discovering framework.
risk-analysis uncertainty-quantification probabilistic-analysis data-mining optimization-algorithms parametric-analysis validation model-reduction model-calibration
Language:C++ 206
BayesWatch / deep-kernel-transfer
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
gaussian-processes few-shot-learning bayesian-methods deep-learning deep-kernel-learning one-shot-learning kernel-methods classification regression gpytorch kernel shot-learning uncertainty-quantification uncertainty paper meta-learning kernels
Language:Python 192
torch-uncertainty
ENSTA-U2IS-AI / torch-uncertainty
Open-source framework for uncertainty and deep learning models in PyTorch :seedling:
bayesian-network computer-vision ensembles mixup neural-networks predictive-uncertainty pytorch reliable-ai trustworthy-machine-learning uncertainty uncertainty-quantification
Language:Python 187
dkogan / mrcal
Next-generation camera-modeling toolkit
camera-calibration lens-modeling structure-from-motion uncertainty-quantification
Language:Python 153
dobriban / Topics-In-Modern-Statistical-Learning
Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc
machine-learning uncertainty-quantification deep-learning conformal-prediction prediction tolerance-intervals calibration
151
Conffusion
eliahuhorwitz / Conffusion
Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.
computer-vision conformal-prediction image-generation image-to-image inpainting quantile-regression super-resolution diffusion-models generative-model deep-learning prediction-intervals pytorch uncertainty-estimation uncertainty-quantification diffusion
Language:Python 131
ykwon0407 / UQ_BNN
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
uncertainty-quantification bayesian-neural-networks
Language:Jupyter Notebook 129
usgs / pestpp
tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis
uncertainty-quantification parameter-estimation ensembles optimization-tools optimization sensitivity-analysis global-sensitivity-analysis parallel-computing non-intrusive ensemble-methods
Language:C++ 118
TorchUQ / torchuq
A library for uncertainty quantification based on PyTorch
pytorch deep-learning uncertainty uncertainty-quantification
Language:Jupyter Notebook 116
Cogito2012 / DEAR
[ICCV 2021 Oral] Deep Evidential Action Recognition
action-recognition debiasing evidential-deep-learning model-calibration ood-detection openset-recognition uncertainty-quantification video-understanding
Language:Python 115
GlacioHack / xdem
Analysis of digital elevation models (DEMs)
dem variogram coregistration geostatistics digital-elevation-model error-analysis surface-elevation-data terrain-analysis uncertainty-quantification python gis
Language:Python 115
SciML / PolyChaos.jl
A Julia package to construct orthogonal polynomials, their quadrature rules, and use it with polynomial chaos expansions.
polynomial-chaos-expansions orthogonal-polynomials quadrature-rules quadrature uncertainty-quantification uncertainty-propagation julia-language quadrature-integration polynomials differential-equations julia scientific-machine-learning
Language:Julia 114
Lingkai-Kong / SDE-Net
Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
deep-learning uncertainty-quantification robustness open-world-classification
Language:Python 102
madsjulia / Mads.jl
MADS: Model Analysis & Decision Support
decision-support model-analysis calibration sensitivity-analysis uncertainty-quantification decision-making model-reduction machine-learning blind-source-separation inversion parameter-estimation high-performance-computing matrix-factorization data-analytics
Language:HTML 101
cics-nd / cnn-surrogate
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
encoder-decoder bayesian-surrogate uncertainty-quantification image-regression stein-variational-gradient-decent
Language:Python 98
nikitadurasov / masksembles
Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
computer-vision deep-learning out-of-distribution-detection paper tensorflow torch uncertainty-estimation uncertainty-neural-networks uncertainty-quantification
Language:Python 94