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cs.LG2025
ReReLRP -- Remembering and Recognizing Tasks with LRP
Karolina Bogacka, Maximilian Höfler, Maria Ganzha +2
Deep neural networks have revolutionized numerous research fields and applications. Despite their widespread success, a fundamental limitation known as catastrophic forgetting rema…
cs.LG2024
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression
Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde +2
Deep Neural Networks are prone to learning and relying on spurious correlations in the training data, which, for high-risk applications, can have fatal consequences. Various approa…