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iNNvestigate Neural Networks!, , , , , , , , , and . J. Mach. Learn. Res., (2019)Pruning by explaining: A novel criterion for deep neural network pruning., , , , , , and . Pattern Recognit., (2021)Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond., , , , , , , and . J. Mach. Learn. Res., (2023)Explainable AI for Time Series via Virtual Inspection Layers., , , and . CoRR, (2023)But that's not why: Inference adjustment by interactive prototype deselection., , , and . CoRR, (2022)Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations., , , , , and . CVPR, page 16143-16152. IEEE, (2023)Opening the machine learning black box with Layer-wise Relevance Propagation.. Technical University of Berlin, Germany, (2019)Generative Fractional Diffusion Models., , , , , , , , , and 1 other author(s). CoRR, (2023)XAI-based Comparison of Input Representations for Audio Event Classification., , , , and . CoRR, (2023)Sanity Checks Revisited: An Exploration to Repair the Model Parameter Randomisation Test., , , and . CoRR, (2024)