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Surrogate Model-Based Explainability Methods for Point Cloud NNs., and . CoRR, (2021)Scheduling Data-Intensive Tasks on Heterogeneous Many Cores., and . IEEE Data Eng. Bull., 42 (1): 61-72 (2019)The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning., , , , , , and . CoRR, (2021)Explainability-Aware One Point Attack for Point Cloud Neural Networks., and . WACV, page 4570-4579. IEEE, (2023)Explainability-Aware One Point Attack for Point Cloud Neural Networks., and . CoRR, (2021)Self-Supervised Source Code Annotation from Related Research Papers., , , and . ICDM (Workshops), page 1083-1084. IEEE, (2021)Yes We Care! - Certification for Machine Learning Methods through the Care Label Framework., , , , , , , , and . CoRR, (2021)Efficient Memory Footprint Reduction., and . Mach. Learn. under Resour. Constraints Vol. 1 (1), De Gruyter, (2022)Yes we care!-Certification for machine learning methods through the care label framework., , , , , , , , and . Frontiers Artif. Intell., (2022)Optimization of ML on Modern Multicore Systems., and . Mach. Learn. under Resour. Constraints Vol. 1 (1), De Gruyter, (2022)