Frequency Analysis

Frequency analysis is a powerful tool increasingly used to understand and improve various machine learning models and data analysis techniques. Current research focuses on leveraging frequency information to enhance model interpretability (e.g., in time series forecasting and image deraining), explain emergent phenomena like "grokking" in neural networks, and improve robustness against adversarial attacks (e.g., in 3D point cloud classification). These applications highlight the significance of frequency analysis in addressing challenges related to model understanding, performance, and security across diverse fields, from authorship attribution to image processing.