Markov processes form a fundamental class of stochastic models in which the evolution of a system is delineated by the memoryless property. In such processes, the future state depends solely on the ...

Semi-Markov processes extend traditional Markov models by explicitly accounting for the time spent in each state before transitioning. This added temporal dimension is particularly valuable in credit ...

We study the evolution of a particle system whose genealogy is given by a supercritical continuous time Galton-Watson tree. The particles move independently according to a Markov process and when a ...

Let $X = (X_t, P^x)$ be a right Markov process and let $m$ be an excessive measure for $X$. Associated with the pair $(X, m)$ is a stationary strong Markov process ...

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving ...

At its core, a Markov chain is a model for predicting the next event in a sequence based only on its state. It possesses ...

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving ...

Prereq., APPM 3570 or equivalent. Same as APPM 4560. Prerequisites: Restricted to Graduate Students only. Usually offered every Fall.

The core of quantum network research lies in efficiently and reliably establishing entanglement between nodes; however, the challenges of maintaining fragile quantum states are far more complex than ...