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Worst-Case Morphs using Wasserstein ALI and Improved MIPGAN., , , , and . CoRR, (2023)Interpreting and Correcting Medical Image Classification with PIP-Net., , , , , and . ECAI Workshops (1), volume 1947 of Communications in Computer and Information Science, page 198-215. Springer, (2023)PIP-Net: Patch-Based Intuitive Prototypes for Interpretable Image Classification., , , and . CVPR, page 2744-2753. IEEE, (2023)Neural Prototype Trees for Interpretable Fine-Grained Image Recognition., , and . CVPR, page 14933-14943. Computer Vision Foundation / IEEE, (2021)Evaluating CNN interpretability on sketch classification., , and . ICMV, volume 11433 of SPIE Proceedings, page 114331Q. SPIE, (2019)Detecting Hacked Twitter Accounts based on Behavioural Change., , and . WEBIST, page 19-31. SciTePress, (2017)This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition., , , and . CoRR, (2020)Neural Prototype Trees for Interpretable Fine-grained Image Recognition., , and . CoRR, (2020)Benchmarking eXplainable AI - A Survey on Available Toolkits and Open Challenges., , , , , and . IJCAI, page 6665-6673. ijcai.org, (2023)This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition., , , and . PKDD/ECML Workshops (1), volume 1524 of Communications in Computer and Information Science, page 441-456. Springer, (2021)