Examples

This is the gallery of examples that showcase the usage of probly. Some examples demonstrate the use of the API in general and some demonstrate specific applications in tutorial form. Also check out our user guide for more detailed illustrations.

Active Learning

Examples concerning the probly.evaluation.active_learning module.

Active Learning with sklearn - Margin vs Random

Active Learning with sklearn - Margin vs Random

Active Learning with PyTorch - BADGE Selection

Active Learning with PyTorch - BADGE Selection

Conformal Prediction

Examples concerning the probly.conformal module.

Regression Conformal Prediction — sklearn

Regression Conformal Prediction — sklearn

Classification Conformal Prediction — sklearn

Classification Conformal Prediction — sklearn

Quantile Regression Conformal Prediction — sklearn

Quantile Regression Conformal Prediction — sklearn

Classification Conformal Prediction — PyTorch

Classification Conformal Prediction — PyTorch

Regression Conformal Prediction — PyTorch

Regression Conformal Prediction — PyTorch

Conformalized Credal Set Prediction — PyTorch.

Conformalized Credal Set Prediction — PyTorch.

Quantile Regression Conformal Prediction — PyTorch

Quantile Regression Conformal Prediction — PyTorch

Integrations

Examples showing how probly can be combined with external uncertainty libraries.

Mixing torch-uncertainty and probly

Mixing torch-uncertainty and probly

Method

Examples concerning the probly.method module.

DARE on Two Moons

DARE on Two Moons

Laplace Approximation on Two Moons

Laplace Approximation on Two Moons

Mahalanobis OOD on Two Moons

Mahalanobis OOD on Two Moons

DUQ on Two Moons

DUQ on Two Moons

DDU on Two Moons

DDU on Two Moons

Het-Net on Two Moons

Het-Net on Two Moons

Credal Net Visualization

Credal Net Visualization

Evidential on Two Moons

Evidential on Two Moons

Credal Wrapper Output Visualization

Credal Wrapper Output Visualization

Credal Ensembling Visualization

Credal Ensembling Visualization

Credal BNN Visualization

Credal BNN Visualization

DARE on MNIST

DARE on MNIST

SNGP Distance Awareness on 2D Toys

SNGP Distance Awareness on 2D Toys

Laplace on MNIST

Laplace on MNIST

Credal BNN on MNIST

Credal BNN on MNIST

Credal Wrapper on MNIST

Credal Wrapper on MNIST

Credal Ensembling on MNIST

Credal Ensembling on MNIST

Credal Net on MNIST

Credal Net on MNIST

SNGP on MNIST

SNGP on MNIST

Mahalanobis OOD on MNIST

Mahalanobis OOD on MNIST

Het-Net on MNIST

Het-Net on MNIST

DUQ on MNIST

DUQ on MNIST

DDU on MNIST

DDU on MNIST

Credal Relative Likelihood Visualization

Credal Relative Likelihood Visualization

Evidential on MNIST

Evidential on MNIST

Credal Relative Likelihood on MNIST

Credal Relative Likelihood on MNIST

DEUP on Two Moons

DEUP on Two Moons

DEUP on MNIST

DEUP on MNIST

Plot

Examples concerning the probly.plot module.

Visualising OOD detection results

Visualising OOD detection results

Plotting credal sets on the simplex

Plotting credal sets on the simplex

Plotting binary credal sets on an interval

Plotting binary credal sets on an interval

Plotting credal sets on a spider (radar) chart

Plotting credal sets on a spider (radar) chart

Pytraverse

Examples concerning the pytraverse module.

A Brief Introduction to PyTraverse

A Brief Introduction to PyTraverse

Quantification

Examples concerning the probly.quantification module.

Uncertainty Quantification

Uncertainty Quantification

Ensemble Regression Uncertainty

Ensemble Regression Uncertainty

Ensemble Ordinal Classification Uncertainty

Ensemble Ordinal Classification Uncertainty

Release Highlights

These examples illustrate the main features of the releases of probly.

Representation

Examples concerning the probly.representation module.

Singleton credal set

Singleton credal set

Convex credal set

Convex credal set

Discrete credal set

Discrete credal set

Distance-based credal set

Distance-based credal set

Probability-intervals credal set

Probability-intervals credal set

Working with ArraySample

Working with ArraySample

Streaming

Examples that combine probly with online learners on data streams. A single representer() + quantify() call gives you the full aleatoric / epistemic / total decomposition on every step of the stream.

Streaming uncertainty with ARFRegressor

Streaming uncertainty with ARFRegressor

Streaming uncertainty with ARFClassifier

Streaming uncertainty with ARFClassifier

MC-Dropout uncertainty on a 2-D stream

MC-Dropout uncertainty on a 2-D stream

Transformation

Examples concerning the probly.transformation module.

DropConnect on Two Moons

DropConnect on Two Moons

Deep Ensemble on Two Moons

Deep Ensemble on Two Moons

MC Dropout on Two Moons

MC Dropout on Two Moons

Natural Posterior Network on Two Moons

Natural Posterior Network on Two Moons

Bayesian Neural Network on Two Moons

Bayesian Neural Network on Two Moons

Posterior Network on Two Moons

Posterior Network on Two Moons

Sub-Ensemble on Two Moons

Sub-Ensemble on Two Moons

Bayesian Ensemble on Two Moons

Bayesian Ensemble on Two Moons

BatchEnsemble on Two Moons

BatchEnsemble on Two Moons

MC Dropout on MNIST

MC Dropout on MNIST

DropConnect on MNIST

DropConnect on MNIST

Deep Ensemble on MNIST

Deep Ensemble on MNIST

Bayesian Neural Network on MNIST

Bayesian Neural Network on MNIST

Natural Posterior Network on MNIST

Natural Posterior Network on MNIST

Bayesian Ensemble on MNIST

Bayesian Ensemble on MNIST

Posterior Network on MNIST

Posterior Network on MNIST

Sub-Ensemble on MNIST

Sub-Ensemble on MNIST

BatchEnsemble on MNIST

BatchEnsemble on MNIST