Samplinglib
Lean gate not recorded for this source state main · ed709a7f320d

Bench overview

Natural-language QA

29 available views. Missing equivalent Lean tasks remain gaps, not borrowed proof credit. Reference answers stay closed until you choose to read them.

Markov Chain Monte Carlo / Discrete Sampling · L3 (provisional)

From atomic balance to reversibility

sogb-001 · 4 rubric points · public-dev

Open question
Optimisation · L3 (provisional)

PL descent: the sign of the contraction factor

sogb-002 · 4 rubric points · public-dev

Open question
Log-Concave Sampling / Optimisation · L2 (provisional)

A quadratic envelope from one midpoint

sogb-003 · 4 rubric points · public-dev

Open question
Statistical Optimal Transport · L3 (provisional)

Wasserstein symmetry without an optimal plan

sogb-004 · 4 rubric points · public-dev

Open question
Riemannian Optimisation · L3 (provisional)

Why a sphere gradient is a projected ambient gradient

sogb-005 · 4 rubric points · public-dev

Open question
Discrete Sampling / Markov Chain Monte Carlo · L3 (provisional)

Null atoms in a random-scan balance proof

sogb-006 · 4 rubric points · public-dev

Open question
SampleWiki research problems / Markov Chain Monte Carlo · L4 (provisional)

Adaptive hybrid error does not certify expected cost

sogb-007 · 4 rubric points · public-dev

Open question
Log-Concave Sampling · L1 (provisional)

A log-concave shape is not yet a probability density

sogb-008 · 4 rubric points · public-dev

Open question
SampleWiki research problems · L1 (provisional)

What kind of guarantee does a sampling claim describe?

sogb-009 · 4 rubric points · public-dev

Open question
Optimisation · L1 (provisional)

Reading a PL inequality before using an algorithm

sogb-010 · 4 rubric points · public-dev

Open question
Riemannian Optimisation · L1 (provisional)

Which space contains the sphere gradient?

sogb-011 · 4 rubric points · public-dev

Open question
Statistical Optimal Transport · L1 (provisional)

What information does a coupling contain?

sogb-012 · 4 rubric points · public-dev

Open question
Discrete Sampling · L1 (provisional)

One random-site step is not one sweep

sogb-013 · 4 rubric points · public-dev

Open question
Markov Chain Monte Carlo · L1 (provisional)

Invariant, reversible and convergent are different claims

sogb-014 · 4 rubric points · public-dev

Open question
Statistical Optimal Transport · L2 (provisional)

Recovering joint probability mass from one marginal

sogb-015 · 4 rubric points · public-dev

Open question
Riemannian Optimisation · L3 (provisional)

A quadratic gradient through the actual sphere differential

sogb-016 · 4 rubric points · public-dev

Open question
SampleWiki research problems / Markov Chain Monte Carlo · L3 (provisional)

Averaging a conditional event-error bound

sogb-017 · 4 rubric points · public-dev

Open question
Statistical Optimal Transport / Log-Concave Sampling · L4 (provisional)

Gluing the right joint law before applying Minkowski

sogb-018 · 4 rubric points · public-dev

Open question
Optimisation · L3 (provisional)

Why a global Lipschitz function bounds its supporting vectors

sogb-019 · 4 rubric points · public-dev

Open question
Optimisation · L3 (provisional)

From subgradient energy to a finite-run best iterate

sogb-020 · 4 rubric points · public-dev

Open question
Markov Chain Monte Carlo / Discrete Sampling · L3 (provisional)

Why retaining one coordinate and conditionally resampling the other is invariant

sogb-021 · 4 rubric points · public-dev

Open question
Riemannian Optimisation / Statistical Optimal Transport · L3 (provisional)

From a selected-curve chord inequality to its first-order bound

sogb-022 · 4 rubric points · public-dev

Open question
Optimisation · L4 (provisional)

An actual gradient flow: objective decay with the zero-curvature branch

sogb-023 · 4 rubric points · public-dev

Open question
Markov Chain Monte Carlo / SampleWiki research problems · L3 (provisional)

One null set for every event, or a different null set for each event?

sogb-024 · 4 rubric points · public-dev

Open question
Log-Concave Sampling / SampleWiki research problems · L3 (provisional)

From Gibbs Poincaré to a directional covariance bound

sogb-025 · 4 rubric points · public-dev

Open question
SampleWiki research problems / Log-Concave Sampling / Optimisation · L4 (provisional)

Can the SPHMC smoothing argument survive weak convexity?

sogb-026 · 4 rubric points · public-dev

Open question
Discrete Sampling / Log-Concave Sampling · L3 (provisional)

Tensorizing a two-point entropy bound without losing the flip constant

sogb-027 · 4 rubric points · public-dev

Open question
Log-Concave Sampling / Discrete Sampling · L4 (provisional)

From the Boolean cube to compact Gaussian log-Sobolev

sogb-028 · 4 rubric points · public-dev

Open question
Optimisation · L3 (provisional)

Chewi Optimization Exercise 3.2: the balanced gradient step

sogb-029 · 4 rubric points · public-dev

Open question