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Code and Appendix of Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping (NeurIPS 2023).

Methods

All the available methods can be found in conf/method

Datasets

All the implemented datasets can be found in conf/data

We uploaded CIFAR10-Reset152 dataset in datasets/ for reproduction. To run with this dataset, the path in conf/cifar10_resnet152.yaml should be modified accordingly.

Run

To run experiments, run "python main.py +method=method_name +data=data_name", for example,

python main.py +method=group_calibration_combine_ts +data=cifar10_resnet152
python main.py +method=group_calibration_combine_ets +data=cifar10_resnet152
python main.py +method=histogram_binning +data=cifar10_resnet152
python main.py +method=isotonic_regression +data=cifar10_resnet152
python main.py +method=temp_scaling +data=cifar10_resnet152
python main.py +method=ets +data=cifar10_resnet152

To verity the performance without calibration, run with method=none:

python main.py +method=none +data=cifar10_resnet152

And the results will be printed.

About

Code and Appendix of Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping (NeurIPS 2023).

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