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Evaluating Recurrent Neural Network Explanations, , , and . Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, page 113--126. Florence, Italy, Association for Computational Linguistics, (August 2019)DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression., , , , , , , , , and 2 other author(s). CoRR, (2019)Understanding Patch-Based Learning by Explaining Predictions., , , and . CoRR, (2018)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)Generative Fractional Diffusion Models., , , , , , , , , and 1 other author(s). CoRR, (2023)Explainable AI for Time Series via Virtual Inspection Layers., , , and . CoRR, (2023)DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology., , , , , , , , , and 3 other author(s). CoRR, (2023)Toward Explainable AI for Regression Models., , , , , and . CoRR, (2021)