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Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation., , , , и . ISBI, стр. 1-5. IEEE, (2022)Visualizing the diversity of representations learned by Bayesian neural networks., , , и . CoRR, (2022)DORA: Exploring outlier representations in Deep Neural Networks., , , , и . CoRR, (2022)Finding Spurious Correlations with Function-Semantic Contrast Analysis., , и . xAI (2), том 1902 из Communications in Computer and Information Science, стр. 549-572. Springer, (2023)ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model., , , , , , и . NeurIPS, (2022)Kidnapping Deep Learning-based Multirotors using Optimized Flying Adversarial Patches., , , , и . MRS, стр. 78-84. IEEE, (2023)How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks., , , , и . CoRR, (2020)Finding the right XAI method - A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science., , , , и . CoRR, (2023)NoiseGrad: enhancing explanations by introducing stochasticity to model weights., , , и . CoRR, (2021)Flying Adversarial Patches: Manipulating the Behavior of Deep Learning-based Autonomous Multirotors., , , и . CoRR, (2023)