Alpha Stable

Alpha-stable distributions are heavy-tailed probability distributions used to model data exhibiting extreme values and deviations from normality, frequently encountered in diverse fields like finance and signal processing. Current research focuses on incorporating alpha-stable noise into various models, including generative neural networks and stochastic differential equations, often employing techniques like distributionally robust optimization and Fourier-space methods for parameter estimation. This work addresses limitations of traditional Gaussian-based approaches by providing more accurate representations of real-world phenomena with heavy-tailed noise, improving model robustness and prediction accuracy in applications ranging from financial modeling to image analysis.