Stochastic Analysis & Random Fields

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Related lectures (22)

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Random Field Ising Model

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

Stochastic Models for Communications

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

Stochastic Models for Communications: Continuous-Time Stochastic Processes

Covers examples of continuous-time stochastic processes in communications.

Conditional Gaussian Generation

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

Continuous-Time Stochastic Processes: Ergodicity Examples

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

Kinetics: Rate Expressions and Mechanisms

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

Safe Learning and Control

Explores safe learning, control, multi-agent coordination, and Nash equilibrium convergence in intelligent systems.

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

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