Divergence (statistics)

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Related lectures (29)

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Vector Fields: Gradient and Divergence

Covers vector fields, gradient, divergence, heat flux, and stress tensors.

Voristicand Characterization of KL Divergences

Explores exploration bias and generalization bound in KL divergences, emphasizing mathematical proofs and implications.

Laplacian: Basics and Examples

Covers the basics of the Laplacian operator applied to scalar fields and its importance in mathematical models.

Equation de continuité

Covers the definition of current density and the general continuity equation with the effect of convection.

Convergence and Divergence: Integrals Analysis

Explores the convergence and divergence of integrals, analyzing their behavior under specific limits.

Quantum Field Theory: Loop Corrections and Counter Terms

Explores loop corrections and counter terms in quantum field theory, showcasing how divergences are handled and predictions are extracted from loop calculations.

Differential Operators: Gradient and Divergence

Introduces differential operators, gradient, and divergence in vector fields.

Model Selection Criteria: AIC, BIC, Cp

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.

Surface Integrals, Divergence Theorem and Stocks' Theorem

Covers surface integrals, the divergence theorem, and Stocks' theorem through examples and analogies.