Frequency analysis is useful for understanding the mechanisms of representation learning
in neural networks (NNs). Most research in this area focuses on the learning dynamics of …

Computer vision models normally witness degraded performance when deployed in real-
world scenarios due to unexpected changes in inputs that were not accounted for during …

In this paper, we use spectral analysis to investigate transfer learning and study model
sensitivity to frequency shortcuts in medical imaging. By analyzing the power spectrum …

Data-driven pre-trained language models typically perform shortcut learning wherein they
rely on the spurious correlations between the data and the ground truth. This reliance can …

Shortcuts, also described as Clever Hans behavior, spurious correlations, or confounders,
present a significant challenge in machine learning and AI, critically affecting model …

In the realm of machine learning, ensuring the robustness of models against adversarial
attacks is critical, particularly in applications such as healthcare, autonomous systems and …

For neural networks, challenges arise when deploying models in real-world scenarios, as
unforeseen changes in inputs can lead to diminished performance. While data …