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Related lectures (26)

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Belief Propagation on Graphs

Covers belief propagation on graphs, exploring computation challenges and heuristics, focusing on sparse random graphs' loop properties.

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.

Martingales and Brownian Motion: Reflected and Absorbed Brownian Motion

Explores the reflected and absorbed Brownian motion transformations and Markov properties.

Latent Space Models: Inference and Applications

Explores latent space models, network representations, spectral decompositions, and parameter estimation methods.

Conditional Gaussian Generation

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

Gaussian Acyclic Models: Linearity and Identifiability

Covers Gaussian Acyclic Models focusing on linearity and identifiability.

Thermodynamic Formalism for Dispersing Billiards

Explores the thermodynamic formalism for dispersing billiards, covering topological entropy, weight functions, and fragmentation lemmas.

Maximum of Gaussians

Explores the p-spin model in spin glass theory and the convergence to the Random Energy Model using Gaussian integrals and the replica method.

Lindblad Equation

Explores the Lindblad equation and the Markov approximation in quantum optics.

Network Inference from Textual Evidence

Delves into network inference from textual evidence, exploring information propagation, translation, and multi-input attention.