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Pruning by explaining: A novel criterion for deep neural network pruning., , , , , , and . Pattern Recognit., (2021)Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations., , , , , and . CVPR, page 16143-16152. IEEE, (2023)Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)., , , and . CVPR Workshops, page 3105-3113. Computer Vision Foundation / IEEE, (2020)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)iNNvestigate Neural Networks!, , , , , , , , , and . J. Mach. Learn. Res., (2019)Explainable AI for time series via Virtual Inspection Layers., , , and . Pattern Recognit., (2024)DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology., , , , , , , , , and 3 other author(s). CoRR, (2023)Generative Fractional Diffusion Models., , , , , , , , , and 1 other author(s). CoRR, (2023)DeepCABAC: Context-adaptive binary arithmetic coding for deep neural network compression., , , , , , , , , and 2 other author(s). CoRR, (2019)