Paper Citation Record · LEDGER

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC

As of 16 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.19186.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.19186 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:48:20.558616Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact3
verified fuzzy30
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6043c334-36f6-44a9-b88c-873984405b8d · outbound

This paper cites The pseudo-marginal approach for efficient Monte Carlo computations.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC The pseudo-marginal approach for efficient Monte Carlo computations

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.867828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e1f8117e-56d5-46ba-bec9-0b9befdd0668 · outbound

This paper cites Explicit constraints on the geometric rate of convergence of random walk Metropolis-Hastings.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Explicit constraints on the geometric rate of convergence of random walk Metropolis-Hastings

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.848199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7f0a9116-27d8-4f06-8695-465c1f3aae0e · outbound

This paper cites Adaptive importance sampling: The past, the present, and the future.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Adaptive importance sampling: The past, the present, and the future

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.802201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 667762d9-6c27-42a0-8c95-f3d2458a6d38 · outbound

This paper cites Computational approaches for empirical Bayes methods and Bayesian sensitivity analysis.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Computational approaches for empirical Bayes methods and Bayesian sensitivity analysis

Reference 4

Resolution: verified exact; doi, observed 2026-08-15T18:48:20.682213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 20ae6c66-38ba-4a0e-a961-423996d10a7c · outbound

This paper cites Markov Chains.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Markov Chains

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.417086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a400a42a-e43b-4a77-bd4e-d5925a0a2548 · outbound

This paper cites Exponential and uniform ergodicity of Markov processes.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Exponential and uniform ergodicity of Markov processes

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.692827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f9002a1-9ca6-4f2f-88ba-bc7b9f02499b · outbound

This paper cites Ethier and Thomas G.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Ethier and Thomas G

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.426664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e67482f-5a47-4bb0-8d9e-1dffe7cdc288 · outbound

This paper cites Importance tempering.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Importance tempering

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.581972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b721c075-b87b-4caa-ab80-f3e8e2c4f4f1 · outbound

This paper cites Optimal mixture weights in multiple importance sampling.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Optimal mixture weights in multiple importance sampling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.434740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4822ae8-f5e2-45b3-93d3-42f32483bbc9 · outbound

This paper cites Convergence of heavy-tailed Monte carlo Markov chain algorithms.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Convergence of heavy-tailed Monte carlo Markov chain algorithms

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.465365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 32dd4d2b-407d-4513-84c9-61a7fe9c5260 · outbound

This paper cites Geometric ergodicity of Metropolis algorithms.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Geometric ergodicity of Metropolis algorithms

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.451913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f4b8c5f-d93e-443d-aa6c-9c64e8f8a5e2 · outbound

This paper cites Jennison.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Jennison

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.439987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9b8cb86b-4a4d-438b-ba57-e6fb2083107d · outbound

This paper cites A course in functional analysis and measure theory.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC A course in functional analysis and measure theory

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.405357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4bfad597-0e08-488c-8a49-8c7b7efc6d7f · outbound

This paper cites Methods of reducing sample size in Monte Carlo computations.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Methods of reducing sample size in Monte Carlo computations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.306731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1e6e7847-4d21-49fb-8a3d-781bd9da13f3 · outbound

This paper cites Importance is Important: Generalized Markov Chain Importance Sampling Methods.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Importance is Important: Generalized Markov Chain Importance Sampling Methods

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.456173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ea093c-9ae9-4cd2-9a29-e608ec85dcc0 · outbound

This paper cites Dynamically weighted importance sampling in Monte Carlo computa- tion.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Dynamically weighted importance sampling in Monte Carlo computa- tion

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.206651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 08f5f335-ee6e-4464-b4e1-19fc6b14d480 · outbound

This paper cites Monte Carlo strategies in scientific computing , volume 10.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Monte Carlo strategies in scientific computing , volume 10

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.192681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9662a58d-5daa-4bd9-a042-e1d095866318 · outbound

This paper cites A theory for dynamic weighting in Monte Carlo computation.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC A theory for dynamic weighting in Monte Carlo computation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.176925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f9166a87-a4eb-44db-90a7-8df539572712 · outbound

This paper cites Foundations of locally-balanced Markov processes.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Foundations of locally-balanced Markov processes

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-15T18:48:20.799351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 349d6d78-8632-41ea-9994-31a329e69899 · outbound

This paper cites Optimality in importance sampling: a gentle survey.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Optimality in importance sampling: a gentle survey

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.476081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68d75f67-7a58-4710-a465-c1de247b4b18 · outbound

This paper cites MCMC-driven importance samplers.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC MCMC-driven importance samplers

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.165552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8cf1990e-869e-413d-9819-6f0b68f3c57d · outbound

This paper cites Simulating ratios of normalizing constants via a simple identity: a theoretical exploration.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Simulating ratios of normalizing constants via a simple identity: a theoretical exploration

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.152397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c49a549c-59dc-46a4-817d-a17b3e69ec4c · outbound

This paper cites Rates of convergence of the Hastings and Metropolis algorithms.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Rates of convergence of the Hastings and Metropolis algorithms

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.140235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a5a93cdb-ba61-42f3-a06e-be72ac78b9ff · outbound

This paper cites Markov chains and stochastic stability.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Markov chains and stochastic stability

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:20.491017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d50cd763-d2ae-45ec-91dd-23496b27060e · outbound

This paper cites Annealed importance sampling.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Annealed importance sampling

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.121035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 84421bbd-2fe1-4312-9d47-1fc21cc26a86 · outbound

This paper cites an unresolved cited work.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:48:21.109256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 50149c95-e88c-4aa2-8b15-5aece81d47cf · outbound

This paper cites Jump Markov chains and rejection-free Metropolis algorithms.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Jump Markov chains and rejection-free Metropolis algorithms

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.097176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation db5d24a4-e44a-4c61-b38d-21dfd4c7fb47 · outbound

This paper cites Selection of proposal distributions for multiple importance sampling.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Selection of proposal distributions for multiple importance sampling

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.077498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a06528ec-5fd8-47e7-bae8-6ffcf05effe5 · outbound

This paper cites Rubinstein.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Rubinstein

Reference 29

Resolution: verified exact; doi, observed 2026-08-15T18:48:20.602207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e0f86ced-d9d6-4169-b887-e18f88891eaf · outbound

This paper cites On a Metropolis–Hastings importance sampling estimator.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC On a Metropolis–Hastings importance sampling estimator

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.050093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ca3b68f0-108d-4929-930b-3298088c6767 · outbound

This paper cites Markov chain importance sampling — a highly efficient estimator for MCMC.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Markov chain importance sampling — a highly efficient estimator for MCMC

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.036778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d41aefe6-f5c1-4713-8917-89f273b72d1b · outbound

This paper cites Sur les fonctions d’ensemble additives et continues.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Sur les fonctions d’ensemble additives et continues

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.018047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b3003ae6-4a69-4ba5-b480-e090c1b4f937 · outbound

This paper cites Honest importance sampling with multiple Markov chains.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Honest importance sampling with multiple Markov chains

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:21.005672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1e4a33bd-4e44-4982-b341-9ea0140cd856 · outbound

This paper cites Optimally combining sampling techniques for Monte Carlo rendering.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Optimally combining sampling techniques for Monte Carlo rendering

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.982580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 98f6b0d2-e6de-41b7-b3d5-8bb340de65e0 · outbound

This paper cites Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.968779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 12c67092-096a-4f14-884f-00cc5f430d99 · outbound

This paper cites Complexity results for MCMC derived from quan- titative bounds.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Complexity results for MCMC derived from quan- titative bounds

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.946184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 2da7444e-48c6-4f21-8f38-44cc616b6293 · outbound

This paper cites Stereographic Markov chain Monte Carlo.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Stereographic Markov chain Monte Carlo

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.932977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c8bdbbfe-473f-4757-b41d-a3eca2bf4fb8 · outbound

This paper cites On the computational com- plexity of high-dimensional Bayesian variable selection.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC On the computational com- plexity of high-dimensional Bayesian variable selection

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.914361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4d5d4711-57f0-4780-a3cd-415426463399 · outbound

This paper cites Scalable importance tempering and Bayesian variable selection.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Scalable importance tempering and Bayesian variable selection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.897802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c1793fb6-033b-44ad-a78a-47d6f7934ba5 · outbound

This paper cites Rapid convergence of informed importance tempering.

From Minimax Optimal Importance Sampling to Uniformly Ergodic Importance-tempered MCMC Rapid convergence of informed importance tempering

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:48:20.871037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.