Topic: Gaussian Conditioning and Linear Maps

Independent-Innovation Representations of Gaussian Blocks

How Conditioning Reduces Gaussian Covariance

Gaussian Regression Residuals and Independence

Gaussian Laws Given Linear Observations

Gaussian Conditioning After Affine Reparameterization

Gaussian Conditioning With Measurement Noise

Deriving Conditional Normal Laws by Completing the Square

Conditioning on Singular Gaussian Blocks

Conditioning Through the Gaussian Precision Matrix

Conditioning Gaussian Vectors on Sums and Contrasts