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Fast and Stable Adversarial Training through Noise Injection., and . CoRR, (2020)Raising the Bar for Certified Adversarial Robustness with Diffusion Models., , , , and . CoRR, (2023)Detektion, Quantifikation und Mitigation von Robustheitsanfälligkeiten in Tiefen Neuronalen Netzen.. University of Erlangen-Nuremberg, Germany, (2023)CLIP: Cheap Lipschitz Training of Neural Networks., , , , and . SSVM, volume 12679 of Lecture Notes in Computer Science, page 307-319. Springer, (2021)System Design for a Data-driven and Explainable Customer Sentiment Monitor., , , , , , , , , and 1 other author(s). CoRR, (2021)Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space., , , , and . CoRR, (2024)Exploring misclassifications of robust neural networks to enhance adversarial attacks., , , , and . Appl. Intell., 53 (17): 19843-19859 (September 2023)Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention., , , and . Trans. Mach. Learn. Res., (2022)System Design for a Data-Driven and Explainable Customer Sentiment Monitor Using IoT and Enterprise Data., , , , , , , , , and 1 other author(s). IEEE Access, (2021)Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks., , , , , , and . IJCNN, page 1-8. IEEE, (2023)