Probability Mass Function

A probability mass function (PMF) describes the probability distribution of a discrete random variable, assigning probabilities to each possible outcome. Current research focuses on improving PMF estimation and application in diverse fields, including speaker recognition (where PMF analysis of speech waveforms aids in detecting spoofing), image generation (using PMF-based sampling from autoencoder latent spaces to enhance image realism), and causal inference (employing PMF analysis to distinguish cause and effect in categorical data). These advancements contribute to improved model accuracy, efficiency, and the ability to quantify uncertainty in various applications, ultimately leading to more robust and reliable systems.