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[NeurIPS'23] Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations

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HKU-MedAI/bnn_uncertainty

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Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations

Code implementations for "Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations"

Trainers

Trainers training our method and some of the baselines are provided in ./trainers. Other baselines are included in ./baselines. Users can customize their own trainers and import them in main.py.

Architectures

Both the BNN and frequentist encoder architectures (e.g., LeNet) can be found in the ./models directory. Users can also customize own encoder architectures.

Get Started

Create a yaml config file in the ./configs directory (examples can be found in the same directory), and run the following codes to run an experiment

python main.py

Results will be saved in ./checkpoints.

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[NeurIPS'23] Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations

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