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Data is Overrated: Perceptual Metrics Can Lead Learning in the Absence of Training Data., , , , и . CoRR, (2023)Reconciling Training and Evaluation Objectives in Location Agnostic Surrogate Explainers., , , , и . CIKM, стр. 3833-3837. ACM, (2023)Evaluating Perceptual Distances by Fitting Binomial Distributions to Two-Alternative Forced Choice Data., , и . CoRR, (2024)FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems., , , , , и . J. Open Source Softw., 5 (49): 1904 (2020)Identification, explanation and clinical evaluation of hospital patient subtypes., , , , , , , и . CoRR, (2023)Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance., , , и . CoRR, (2019)Orthonormal Convolutions for the Rotation Based Iterative Gaussianization., , , и . ICIP, стр. 4018-4022. IEEE, (2022)Disentangling the Link Between Image Statistics and Human Perception., , , и . CoRR, (2023)On the relation between statistical learning and perceptual distances., , , , и . CoRR, (2021)bLIMEy: Surrogate Prediction Explanations Beyond LIME., , , и . CoRR, (2019)