Lectures related to Spatial Ergodicity for SPDEs

Explores the application of randomness in physical models, focusing on Brownian motion and diffusion.

Explores the Fokker-Planck and KPZ equations in stochastic processes and random growth models.

Covers Stochastic Calculus, focusing on Itô's Formula, Stochastic Differential Equations, martingale properties, and option pricing.

Covers the essentials of probability, algebras, and conditional probability, including the Borel o-algebra and Poisson processes.

Covers the outcomes of a virtual seminar on stochastic analysis.

Covers Stochastic Differential Equations, Wiener increment, Ito's lemma, and white noise integration in financial modeling.

Explores classical mean field theory, local interactions, and examples like individual-based SIR models and raindrop formation.

Covers linear-quadratic stochastic differential games on directed chain networks and open-loop Nash equilibria.

Covers stochastic models for communications and the estimation of correlation functions.

Covers stochastic integrals, emphasizing isometry and continuity properties in martingales and different spaces.

Explores stochastic processes in continuous time, emphasizing Brownian motion and related concepts.

Explores the derivation of the Fokker-Planck equation and its applications in stochastic differential equations.

Covers recent research on singular SPDEs and their applications in quantum field theory.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Explores nonlinear PDE models with stochastic fractional perturbation, focusing on regularity identification and space-time noise interpretation.

Explores quadratic variation in martingales and stochastic integrals, emphasizing their properties and extensions.

Explores the construction of Brownian motion with continuous trajectories and the dimension of its zero set.

Covers the analysis of speed variation using differential equations and small time intervals.

Covers the Fourier transform, spectral densities, Wiener-Khinchin theorem, and stochastic processes.