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Understanding Patch-Based Learning by Explaining Predictions., , , and . CoRR, (2018)DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression., , , , , , , , , and 2 other author(s). CoRR, (2019)iNNvestigate Neural Networks!, , , , , , , , , and . J. Mach. Learn. Res., (2019)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)Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond., , , , , , , and . J. Mach. Learn. Res., (2023)Pruning by explaining: A novel criterion for deep neural network pruning., , , , , , and . Pattern Recognit., (2021)Estimation of distortion sensitivity for visual quality prediction using a convolutional neural network., , , , and . Digit. Signal Process., (2019)Toward Explainable AI for Regression Models., , , , , and . CoRR, (2021)Explainable AI for Time Series via Virtual Inspection Layers., , , and . CoRR, (2023)Comment on "Solving Statistical Mechanics Using VANs": Introducing saVANt - VANs Enhanced by Importance and MCMC Sampling., , , , , and . CoRR, (2019)