Stationary Mass

Stationary mass, representing the long-term distribution of probabilities in a system, is a key concept across diverse scientific fields. Current research focuses on accurately estimating this mass, particularly in complex systems like Markov chains, using novel algorithms like windowed Good-Turing estimators and deep learning models such as convolutional neural networks. These advancements improve the precision of probability estimations in sequence modeling and enable applications ranging from analyzing protoplanetary discs to identifying cosmic ray composition, ultimately enhancing our understanding of various natural phenomena and improving the performance of AI systems.