Tutorials¶
On this page, you will find tutorials and insights on TorchUncertainty. Don’t hesitate to open an issue if you have any question or suggestion for tutorials.

Improve Top-label Calibration with Temperature Scaling
Improve Top-label Calibration with Temperature Scaling

Training a LeNet with Monte Carlo Batch Normalization
Training a LeNet with Monte Carlo Batch Normalization

Corrupting Images with TorchUncertainty to Benchmark Robustness
Corrupting Images with TorchUncertainty to Benchmark Robustness

Improved Ensemble parameter-efficiency with Packed-Ensembles
Improved Ensemble parameter-efficiency with Packed-Ensembles