8.1 · Book p. 215 · PDF p. 227
Introduction to the Proximal Sampler
Introduces the Gaussian augmentation and alternating conditional updates defining the proximal sampler.
Open this section in the canonical August 9 source ↗Why is this valid?
Before composing kernels, both conditional normalizers must be measurable, positive, and finite.
Source assumptions
- well-defined conditional samplers
Formal assumptions
- kernel measurability
- finite conditional normalizers
- joint-law marginal identity
View Lean formalization
ASTIS treats kernel measurability, normalization, Fubini/Tonelli, and marginal preservation as independent reusable roots.
No ASTIS-owned declaration is mapped yet.
Downstream consumers
- proximal sampler convergence
- structured sampling