: A specialized version of the chain rule that accounts for the "jumps" in the process.

: Recent research uses Lévy-driven SDEs to improve the performance of non-convex optimization and Bayesian learning algorithms. Lévy Processes and Stochastic Calculus

Traditional calculus fails when dealing with the non-differentiable paths of random processes. Stochastic calculus provides the tools to integrate and differentiate these paths, which is critical for:

: Generalizes the Poisson process by allowing jumps of random sizes.

And Stochastic Calculus: Levy Processes

: A specialized version of the chain rule that accounts for the "jumps" in the process.

: Recent research uses Lévy-driven SDEs to improve the performance of non-convex optimization and Bayesian learning algorithms. Lévy Processes and Stochastic Calculus

Traditional calculus fails when dealing with the non-differentiable paths of random processes. Stochastic calculus provides the tools to integrate and differentiate these paths, which is critical for:

: Generalizes the Poisson process by allowing jumps of random sizes.