Showing 1 open source project for "deep learning"

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    Uncertainty Baselines

    Uncertainty Baselines

    High-quality implementations of standard and SOTA methods

    ...Techniques include deep ensembles, Monte Carlo dropout, temperature scaling, stochastic variational inference, heteroscedastic heads, and out-of-distribution detection workflows. Each baseline emphasizes reproducibility: fixed seeds, standard splits, and strong metrics such as calibration error, AUROC for OOD, and accuracy under shift.
    Downloads: 0 This Week
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