Brownian Motion

Brownian motion, the random movement of particles suspended in a fluid, is a fundamental stochastic process with applications across diverse scientific fields. Current research focuses on leveraging Brownian motion in advanced modeling techniques, including diffusion models for generative tasks and neural network-based approaches for learning and simulating complex systems exhibiting Brownian dynamics, often incorporating graph neural networks or stochastic differential equations. These advancements are improving the accuracy and efficiency of simulations in areas such as biostatistics, materials science, and machine learning, enabling better understanding and prediction of complex systems.