Samplinglib
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Samplinglib · seven first-class libraries

One formal graph across sampling and optimisation.

Public mathematical sources provide stable coordinate systems; SampleWiki inserts frontier results into the same reusable theorem graph.

Textbook

Log-Concave Sampling

Chewi's source-aligned textbook graph, including the official Chapter 2 supplement.

Open textbook
Research frontier

SampleWiki

Source-pinned frontier results inserted into the reusable graph.

Open SampleWiki
Chapter scaffold

Riemannian Optimization

Boumal's eleven-chapter geometry and optimization route.

Open library
Public arXiv notes + upstream reuse

Optimisation

Formalising Sinho Chewi's Lectures on Optimization, with Mathlib, Optlib and CvxLean searched before new proofs.

Open library
Chapter scaffold

Statistical Optimal Transport

Chewi, Niles-Weed and Rigollet: eight chapters and two appendices, with shared transport, convexity and probability foundations.

Open library
Finite-state source scaffold

Discrete Sampling

Ising/Glauber, hard-core and matroid sampling. Chen, Štefankovič and Vigoda, with complementary model and mixing-time sources.

Open library
Method-family source scaffold

Markov Chain Monte Carlo

Scalable Monte Carlo for Bayesian Learning: six primary chapters, with source-pinned extended reading paths.

Open library
Truth boundary. Scaffold means public chapter routes and source boundaries, not completed Lean proofs.