Lectures related to Stochastic Analysis & Random Fields

Spatial Ergodicity for SPDEs

Explores spatial ergodicity for SPDEs, covering basic formulations, initial data effects, and results on ergodicity and CLT.

Stochastic Games on Directed Networks

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

Mean Field Theory: Stochastic Analysis and Applications

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

Virtual Seminar on Stochastic Analysis

Introduces a virtual seminar on stochastic analysis, covering a wide range of topics and focusing on the mathematical challenges of the COVID-19 crisis.

Fokker-Planck & KPZ Equations

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

Maximum Entropy Principle: Stochastic Differential Equations

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

Random Field Ising Model

Covers the Random Field Ising Model, discussing the concept of disorder and the process of finding the ground state.

Kinetics: Rate Expressions and Mechanisms

Explores rate expressions, steady-state approximation, and reaction simulation algorithms using random numbers.

Debiased Whittle Likelihood: Time Series and Spatial Data

Explores the Debiased Whittle likelihood for time series and spatial data, focusing on fitting spectral density to the periodogram for better predictions and parameter estimation.

Stochastic Analysis & Epidemic Containment Models

Delves into stochastic analysis, contract theory, and epidemic models, exploring uncertainties and interventions in epidemiology.

Energy landscape: Symmetric Interactions MOOC: Neuronal Dynamics 2- Computational Neuroscience: Neuronal Dynamics of Cognition

Explores the energy landscape in symmetric interactions, emphasizing the importance of symmetric weights and random patterns.

Global Sensitivity Analysis in Stochastic Systems

On Variance-Based Sensitivity Analysis for Stochastic Systems covers the impact of parameters uncertainty and sensitivity indices in stochastic models.

Rainfall Models: Deterministic vs Stochastic Log in to Mediaspace to watch this video

Covers deterministic and stochastic rainfall models in water resources engineering, including generation, calibration, and spatially explicit models.

Linear Prediction and Estimation Log in to Mediaspace to watch this video

Explores linear prediction, optimal filters, random signals, stationarity, autocorrelation, power spectral density, and Fourier transform in signal processing.

L-Systems: Understanding and Applications Log in to Mediaspace to watch this video

Covers the basics of L-Systems, explores various examples, discusses stochastic variations, and extends to 3D modeling.

Markov Chains: Theory and Applications Log in to Mediaspace to watch this video

Covers the theory and applications of Markov chains in modeling random phenomena and decision-making under uncertainty.

Stochastic Models for Communications Log in to Mediaspace to watch this video

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

Stochastic Models for Communications: Continuous-Time Stochastic Processes Log in to Mediaspace to watch this video

Covers examples of continuous-time stochastic processes in communications.

Conditional Gaussian Generation Log in to Mediaspace to watch this video

Explores the generation of multivariate Gaussian distributions and the challenges of factorizing covariance matrices.

Continuous-Time Stochastic Processes: Ergodicity Examples Log in to Mediaspace to watch this video

Covers examples of ergodicity in continuous-time stochastic processes, illustrating concepts such as ergodicity and random processes.