Conveners
Probability and Statistics
- Susanne Saminger-Platz
Piecewise diffusion Markov processes (PDifMPs) form a versatile class of stochastic hybrid systems that combine continuous diffusion processes with discrete event-driven dynamics, enabling flexible modelling of complex real-world hybrid phenomena. The practical utility of PDifMP models, however, depends critically on accurate estimation of their underlying parameters. In this work, we present...
In this talk, we study the long-time behaviour of second-order Langevin dynamics and establish global contraction in an $L^1$-Wasserstein distance with an explicit dimension-free rate. The contraction result is not restricted to forces corresponding to strongly convex confining potentials. It rather includes multi-well potentials and non-gradient-type forces. In the proof, we use a coupling...
Piecewise Diffusion Markov Processes (PDifMPs) are valuable for modelling systems where continuous dynamics are interrupted by sudden shifts and/or changes in drift and diffusion. The first-passage time (FPT) in such models plays a central role in understanding when a process first reaches a critical boundary. In many systems, time-dependent thresholds provide a flexible framework for...