CIFAR10 statistics and PCA
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CIFAR10 mean (mean_reshaped.npy) and standard deviation (std_reshaped.npy) calculated on the training set; CIFAR10's covariance matrix's eigenvalues (eigenvalues.npy), the ratio of total variance explained by each principal component (eigenvalues_ratio.npy), eand CIFAR10's principal components (pc_matrix.npy) computed using the normalized training dataset. These items were used in [1]. [1] Alice Bizeul, Thomas M. Sutter, Alain Ryser, Julius Von Kügelgen, Bernhard Schölkopf, Julia E. Vogt. Components Beat Patches: Eigenvector Masking for Visual Representation Learning. Oct, 2024.
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Zenodo创建时间:
2025-01-02



