Probabilistic Robustness Assessment of Pre-Northridge Steel Moment Resisting Frames
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New adversarial attacks target deep reinforcement learning-based intrusion detection systems
Researchers have developed new methods for generating universal adversarial perturbations (UAPs) specifically designed to degrade the performance of deep reinforcement learning (DRL)-based intrusion detection systems (I…
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New metric for AI trustworthiness in medical imaging unveiled
Researchers have introduced probabilistic robustness (PR) as a more practical measure for assessing the trustworthiness of deep learning models in medical image classification. This approach contrasts with existing adve…
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New NPPR metric offers robust deep learning evaluation
Researchers have introduced Non-Parametric Probabilistic Robustness (NPPR), a new metric for evaluating the robustness of deep learning models. Unlike previous methods that assume a known perturbation distribution, NPPR…
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New benchmarks and frameworks advance AI model robustness evaluation
Researchers have introduced PRBench, a new benchmark designed to standardize the evaluation of probabilistic robustness in deep learning models. This benchmark compares various adversarial training (AT) and probabilisti…