Paper Citation Record · LEDGER

Provable Diffusion Posterior Sampling for Bayesian Inversion

As of 22 August 2026, this Paper Citation Record lists 100 of 150 outbound references and 4 inbound Pith citation observations for arXiv:2512.08022.

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

pith.paper-citation-record.v1
2512.08022 v2

Coverage vector

measured 100 of 150 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T17:55:19.454079Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T02:44:16.521945Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:56:55.555732Z

Reference resolution

100 of 150 outbound references displayed

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verified fuzzy0
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External citation measurements

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Outbound references

Observation 632cfa14-2b35-45a9-ad81-981f88dec42f · outbound

This paper cites Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo.

Provable Diffusion Posterior Sampling for Bayesian Inversion Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:10.818304Z

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Observation a512b8aa-4eb3-40bd-a7a0-48792f48326a · outbound

This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

Provable Diffusion Posterior Sampling for Bayesian Inversion Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:10.929621Z

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Observation 4822dab1-8ec4-41d2-b305-4d350e4d379d · outbound

This paper cites Building normalizing flows with stochastic interpolants.

Provable Diffusion Posterior Sampling for Bayesian Inversion Building normalizing flows with stochastic interpolants

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.043570Z

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Observation d48f3244-ceb3-42cf-a409-c49a5f094577 · outbound

This paper cites Reverse-time diffusion equation models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Reverse-time diffusion equation models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.111619Z

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Observation 74c06ba0-7d8b-4fd3-b09e-d8eaad7c2484 · outbound

This paper cites Uncertainty estimation for computed tomography with a linearised deep image prior.

Provable Diffusion Posterior Sampling for Bayesian Inversion Uncertainty estimation for computed tomography with a linearised deep image prior

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.251675Z

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Observation 620f18ea-7ec4-414c-807d-3143ed413692 · outbound

This paper cites Wasserstein generative adversarial networks.

Provable Diffusion Posterior Sampling for Bayesian Inversion Wasserstein generative adversarial networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.308469Z

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Observation 73095447-d937-4d07-995d-a7f5166678ae · outbound

This paper cites Machine learning for inverse problems and data assimilation, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Machine learning for inverse problems and data assimilation, 2025

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.328572Z

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Observation 2064f70a-d300-4736-abb3-0f943673e331 · outbound

This paper cites Variationally correct neural residual regression for parametric pdes: on the viability of controlled accuracy.

Provable Diffusion Posterior Sampling for Bayesian Inversion Variationally correct neural residual regression for parametric pdes: on the viability of controlled accuracy

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.367359Z

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Observation 99f8c557-ab02-4e17-bf82-e2be0431b372 · outbound

This paper cites Diffusions hypercontractives.

Provable Diffusion Posterior Sampling for Bayesian Inversion Diffusions hypercontractives

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.422620Z

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Observation e786f11f-3e11-4ddc-a995-71d963802694 · outbound

This paper cites Analysis and Geometry of Markov Diffusion Operators, volume 348 of Grundlehren der mathematischen Wissenschaften (GL).

Provable Diffusion Posterior Sampling for Bayesian Inversion Analysis and Geometry of Markov Diffusion Operators, volume 348 of Grundlehren der mathematischen Wissenschaften (GL)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.547578Z

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Observation 78b9c5b1-e598-458b-a3bf-33a01a057bbd · outbound

This paper cites Universal guidance for diffusion models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Universal guidance for diffusion models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.709367Z

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Observation 95c23d0a-d107-46c8-96d8-5fee7b1a151b · outbound

This paper cites A score-based filter for nonlinear data assimilation.

Provable Diffusion Posterior Sampling for Bayesian Inversion A score-based filter for nonlinear data assimilation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.816236Z

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Observation 1a324243-b170-4312-9231-84ccf90fa36a · outbound

This paper cites On Deep Learning as a Remedy for the Curse of Dimensionality in Nonparametric Regression.

Provable Diffusion Posterior Sampling for Bayesian Inversion On Deep Learning as a Remedy for the Curse of Dimensionality in Nonparametric Regression

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.862675Z

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Observation 90782ec6-0ef9-4bbb-a331-599be39e5011 · outbound

This paper cites Modern regularization methods for inverse problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Modern regularization methods for inverse problems

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.915623Z

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Observation 1b37dca7-2130-4236-85b0-eae0b3fddd3c · outbound

This paper cites Convergence of deterministic and stochastic diffusion-model samplers: A simple analysis in wasserstein distance, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Convergence of deterministic and stochastic diffusion-model samplers: A simple analysis in wasserstein distance, 2025

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:11.976333Z

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Observation 98bc0b16-ae97-478c-816b-40577a17b2f1 · outbound

This paper cites Bayesian inversion for nonlinear imaging models using deep generative priors.

Provable Diffusion Posterior Sampling for Bayesian Inversion Bayesian inversion for nonlinear imaging models using deep generative priors

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.037373Z

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Observation 862bf33f-8295-4d60-a13b-603d40755d0e · outbound

This paper cites Provable posterior sampling with denoising oracles via tilted transport.

Provable Diffusion Posterior Sampling for Bayesian Inversion Provable posterior sampling with denoising oracles via tilted transport

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.100341Z

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Observation 4024d6c7-d8a4-464b-8ca8-a340a9e1951a · outbound

This paper cites Nf-ula: Normalizing flow-based unadjusted langevin algorithm for imaging inverse problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Nf-ula: Normalizing flow-based unadjusted langevin algorithm for imaging inverse problems

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.313667Z

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Observation d5afa08a-1366-4fb7-b5cb-f6d1ec53a9dd · outbound

This paper cites Monte carlo guided denoising diffusion models for bayesian linear inverse problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Monte carlo guided denoising diffusion models for bayesian linear inverse problems

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.385669Z

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Observation 518fc006-a9a2-4b86-9f78-f5a4df092d89 · outbound

This paper cites Deep conditional distribution learning via conditional F \"ollmer flow, 2024.

Provable Diffusion Posterior Sampling for Bayesian Inversion Deep conditional distribution learning via conditional F \"ollmer flow, 2024

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.490493Z

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Observation 397e5bca-5051-4b8a-9ab0-9f9d49002cf5 · outbound

This paper cites Neural sampling from boltzmann densities: Fisher-rao curves in the wasserstein geometry.

Provable Diffusion Posterior Sampling for Bayesian Inversion Neural sampling from boltzmann densities: Fisher-rao curves in the wasserstein geometry

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.709085Z

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Observation b5c45e76-5074-49cb-aa47-7733accb8116 · outbound

This paper cites Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach.

Provable Diffusion Posterior Sampling for Bayesian Inversion Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.766390Z

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Observation e5dd82af-5dbe-4a96-b335-41cc501dafec · outbound

This paper cites Dimension-free log- S obolev inequalities for mixture distributions.

Provable Diffusion Posterior Sampling for Bayesian Inversion Dimension-free log- S obolev inequalities for mixture distributions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.832915Z

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Observation 3fa6429a-66ec-4166-9335-103ead14292d · outbound

This paper cites Improved analysis of score-based generative modeling: U ser-friendly bounds under minimal smoothness assumptions.

Provable Diffusion Posterior Sampling for Bayesian Inversion Improved analysis of score-based generative modeling: U ser-friendly bounds under minimal smoothness assumptions

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:12.892938Z

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Observation 7a5731b0-e15b-48dd-aab6-8b6e01f8686b · outbound

This paper cites Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks.

Provable Diffusion Posterior Sampling for Bayesian Inversion Distribution Approximation and Statistical Estimation Guarantees of Generative Adversarial Networks

Reference 25

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Observation ed8d1fdd-19a1-4de8-b751-1d19bd63722a · outbound

This paper cites The probability flow ode is provably fast.

Provable Diffusion Posterior Sampling for Bayesian Inversion The probability flow ode is provably fast

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:13.041360Z

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Observation f3dfaf17-b804-46a2-a884-4ce6568ec131 · outbound

This paper cites Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.

Provable Diffusion Posterior Sampling for Bayesian Inversion Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions

Reference 27

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Observation b0a28adc-94e6-4184-b2dc-ee2700eab1db · outbound

This paper cites Diffusive G ibbs sampling.

Provable Diffusion Posterior Sampling for Bayesian Inversion Diffusive G ibbs sampling

Reference 28

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Observation c9bc9237-6838-4659-95a3-698033a23c15 · outbound

This paper cites Efficient, multimodal, and derivative-free bayesian inference with fisher-rao gradient flows.

Provable Diffusion Posterior Sampling for Bayesian Inversion Efficient, multimodal, and derivative-free bayesian inference with fisher-rao gradient flows

Reference 29

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Observation 909a33d7-ee20-4740-b5b7-0740686a14f1 · outbound

This paper cites Erdogdu, Mufan Li, Ruoqi Shen, and Matthew S.

Provable Diffusion Posterior Sampling for Bayesian Inversion Erdogdu, Mufan Li, Ruoqi Shen, and Matthew S

Reference 30

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Observation aeb6f026-2f09-4e3a-b2aa-29b652f345ff · outbound

This paper cites What does guidance do? a fine-grained analysis in a simple setting.

Provable Diffusion Posterior Sampling for Bayesian Inversion What does guidance do? a fine-grained analysis in a simple setting

Reference 31

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Observation d225ed0d-8c7c-45a4-a7ab-8a198fea7369 · outbound

This paper cites Stargan v2: Diverse image synthesis for multiple domains.

Provable Diffusion Posterior Sampling for Bayesian Inversion Stargan v2: Diverse image synthesis for multiple domains

Reference 32

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Observation 2ce2cfe4-6d71-414c-b30f-ed132a0323d4 · outbound

This paper cites Split gibbs discrete diffusion posterior sampling, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Split gibbs discrete diffusion posterior sampling, 2025

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:13.618907Z

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Observation 29aeb6ed-0936-4a99-959e-ebb0f80efe56 · outbound

This paper cites Improving diffusion models for inverse problems using manifold constraints.

Provable Diffusion Posterior Sampling for Bayesian Inversion Improving diffusion models for inverse problems using manifold constraints

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:13.719812Z

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Observation 8404d901-10bc-4a62-b022-795cc27de63e · outbound

This paper cites Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction.

Provable Diffusion Posterior Sampling for Bayesian Inversion Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction

Reference 35

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Observation 7732c1c1-5d32-477c-a247-a03fb173e7a1 · outbound

This paper cites Diffusion posterior sampling for general noisy inverse problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Diffusion posterior sampling for general noisy inverse problems

Reference 36

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Observation 3ce673e2-29e8-48b4-a1ba-78d20f4a0e0f · outbound

This paper cites CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

Provable Diffusion Posterior Sampling for Bayesian Inversion CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Reference 37

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Observation 00353469-fe4a-4e46-bf15-ac08e0ced69d · outbound

This paper cites Plug-and-play split gibbs sampler: Embedding deep generative priors in bayesian inference.

Provable Diffusion Posterior Sampling for Bayesian Inversion Plug-and-play split gibbs sampler: Embedding deep generative priors in bayesian inference

Reference 38

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Observation 5d6f5f86-0c74-4b27-8dc4-1f2d4e69a194 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 39

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Observation 1660b569-22e0-4470-b556-cfbf35e601b8 · outbound

This paper cites Theoretical guarantees for approximate sampling from smooth and log-concave densities.

Provable Diffusion Posterior Sampling for Bayesian Inversion Theoretical guarantees for approximate sampling from smooth and log-concave densities

Reference 40

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Observation a6ffa5a6-201c-4259-bfc9-f0c257a9f757 · outbound

This paper cites Patel, Deep Ray, Erik A.

Provable Diffusion Posterior Sampling for Bayesian Inversion Patel, Deep Ray, Erik A

Reference 41

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 42

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Observation f2822045-131a-4a2c-9a5a-aae866730e1a · outbound

This paper cites Diffusion models beat GAN s on image synthesis.

Provable Diffusion Posterior Sampling for Bayesian Inversion Diffusion models beat GAN s on image synthesis

Reference 43

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Observation 6c4447a2-dc70-4a7c-aaa3-e200a18ff288 · outbound

This paper cites Sampling via F\"ollmer Flow.

Provable Diffusion Posterior Sampling for Bayesian Inversion Sampling via F\"ollmer Flow

Reference 44

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Observation 4d9b1323-5a8d-4b38-9bd4-9d697fd6abea · outbound

This paper cites Characteristic learning for provable one step generation, 2024 a.

Provable Diffusion Posterior Sampling for Bayesian Inversion Characteristic learning for provable one step generation, 2024 a

Reference 45

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Observation 0f069e2b-054d-4b89-8796-bfa45300e416 · outbound

This paper cites Nonlinear Assimilation via Score-based Sequential Langevin Sampling.

Provable Diffusion Posterior Sampling for Bayesian Inversion Nonlinear Assimilation via Score-based Sequential Langevin Sampling

Reference 46

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Source-reported events for the cited work

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Observation 5765bf09-7d67-464c-b4ca-b7310bc005db · outbound

This paper cites Semi-supervised deep sobolev regression: E stimation and variable selection by ReQU neural network.

Provable Diffusion Posterior Sampling for Bayesian Inversion Semi-supervised deep sobolev regression: E stimation and variable selection by ReQU neural network

Reference 47

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Observation 69589597-a9c8-4b16-a222-d49bcdba979d · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 48

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Source-reported events for the cited work

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Observation 289c9621-3121-41c7-9b5f-177fad9e40d7 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Statistics and Information Theory

Reference 49

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Observation 875c389f-c6c2-4a37-bc2b-e1354aedb9c3 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Telegrapher's Generative Model via Kac Flows

Reference 50

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Observation 57aaa489-2142-46a7-bd8a-4eda3b09a543 · outbound

This paper cites A proximal markov chain monte carlo method for bayesian inference in imaging inverse problems: When langevin meets moreau.

Provable Diffusion Posterior Sampling for Bayesian Inversion A proximal markov chain monte carlo method for bayesian inference in imaging inverse problems: When langevin meets moreau

Reference 51

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Observation b42bb10e-a349-479e-9059-997ca39a4de4 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 52

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Observation 17fa6cb3-7197-46a9-9e3f-ba8de13deab2 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 53

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Observation 52d86382-dcaa-45ed-be12-d4ef05857bd5 · outbound

This paper cites Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory.

Provable Diffusion Posterior Sampling for Bayesian Inversion Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory

Reference 54

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Observation 449e308f-b378-4c32-9e90-82a5f90260db · outbound

This paper cites Learn to guide your diffusion model, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Learn to guide your diffusion model, 2025

Reference 55

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Observation 15d5a2a4-ea40-4489-aca1-493f5d5d1c28 · outbound

This paper cites Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference.

Provable Diffusion Posterior Sampling for Bayesian Inversion Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference

Reference 56

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Observation 952d1f81-5a0d-47af-94ea-bfec86d25724 · outbound

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Provable Diffusion Posterior Sampling for Bayesian Inversion Generative adversarial nets

Reference 57

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Observation da17e6ca-d446-462e-9a93-538f9dfadc59 · outbound

This paper cites Stochastic localization via iterative posterior sampling.

Provable Diffusion Posterior Sampling for Bayesian Inversion Stochastic localization via iterative posterior sampling

Reference 58

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Observation 5b5b91f6-028f-435b-9c09-cf373830748d · outbound

This paper cites Improved training of W asserstein GANs.

Provable Diffusion Posterior Sampling for Bayesian Inversion Improved training of W asserstein GANs

Reference 59

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Observation c5ab7983-eefa-44f1-aa84-5df67dad8e7d · outbound

This paper cites Proximal Diffusion Neural Sampler.

Provable Diffusion Posterior Sampling for Bayesian Inversion Proximal Diffusion Neural Sampler

Reference 60

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This paper cites Provable benefit of annealed langevin monte carlo for non-log-concave sampling.

Provable Diffusion Posterior Sampling for Bayesian Inversion Provable benefit of annealed langevin monte carlo for non-log-concave sampling

Reference 61

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This paper cites Gradient guidance for diffusion models: An optimization perspective.

Provable Diffusion Posterior Sampling for Bayesian Inversion Gradient guidance for diffusion models: An optimization perspective

Reference 62

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This paper cites Sur les probl \`e mes aux d \'e riv \'e es partielles et leur signification physique.

Provable Diffusion Posterior Sampling for Bayesian Inversion Sur les probl \`e mes aux d \'e riv \'e es partielles et leur signification physique

Reference 63

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This paper cites Zeroth-order sampling methods for non-log-concave distributions: Alleviating metastability by denoising diffusion.

Provable Diffusion Posterior Sampling for Bayesian Inversion Zeroth-order sampling methods for non-log-concave distributions: Alleviating metastability by denoising diffusion

Reference 64

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Observation 07c5892c-c1e7-49de-9805-86f1e9a9e524 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Provable Diffusion Posterior Sampling for Bayesian Inversion Classifier-Free Diffusion Guidance

Reference 65

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Observation 53834745-1590-4351-a8ee-66bd4d20e50e · outbound

This paper cites Denoising diffusion probabilistic models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Denoising diffusion probabilistic models

Reference 66

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Observation 910c069f-8064-4b43-9b55-89c8a41c1230 · outbound

This paper cites Convergence analysis of probability flow ode for score-based generative models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Convergence analysis of probability flow ode for score-based generative models

Reference 67

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This paper cites An error analysis of generative adversarial networks for learning distributions.

Provable Diffusion Posterior Sampling for Bayesian Inversion An error analysis of generative adversarial networks for learning distributions

Reference 68

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Observation 4be2bce6-6b69-4cdb-9134-6f5ce926541d · outbound

This paper cites o dinger-f \.

Provable Diffusion Posterior Sampling for Bayesian Inversion o dinger-f \

Reference 69

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Observation 6b331057-aa30-4d33-8a57-d278434950ad · outbound

This paper cites Reverse diffusion M onte C arlo.

Provable Diffusion Posterior Sampling for Bayesian Inversion Reverse diffusion M onte C arlo

Reference 70

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This paper cites Faster sampling without isoperimetry via diffusion-based monte carlo.

Provable Diffusion Posterior Sampling for Bayesian Inversion Faster sampling without isoperimetry via diffusion-based monte carlo

Reference 71

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This paper cites Estimation of non-normalized statistical models by score matching.

Provable Diffusion Posterior Sampling for Bayesian Inversion Estimation of non-normalized statistical models by score matching

Reference 72

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This paper cites Inverse Problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Inverse Problems

Reference 73

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This paper cites Bridging diffusion posterior sampling and monte carlo methods: a survey.

Provable Diffusion Posterior Sampling for Bayesian Inversion Bridging diffusion posterior sampling and monte carlo methods: a survey

Reference 74

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This paper cites Simulation-based Inference via Langevin Dynamics with Score Matching.

Provable Diffusion Posterior Sampling for Bayesian Inversion Simulation-based Inference via Langevin Dynamics with Score Matching

Reference 75

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This paper cites Towards a unified framework for guided diffusion models, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Towards a unified framework for guided diffusion models, 2025

Reference 76

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This paper cites Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors.

Provable Diffusion Posterior Sampling for Bayesian Inversion Deep nonparametric regression on approximate manifolds: Nonasymptotic error bounds with polynomial prefactors

Reference 77

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This paper cites A style-based generator architecture for generative adversarial networks.

Provable Diffusion Posterior Sampling for Bayesian Inversion A style-based generator architecture for generative adversarial networks

Reference 78

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This paper cites Elucidating the design space of diffusion-based generative models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Elucidating the design space of diffusion-based generative models

Reference 79

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This paper cites Solving linear-gaussian bayesian inverse problems with decoupled diffusion sequential monte carlo.

Provable Diffusion Posterior Sampling for Bayesian Inversion Solving linear-gaussian bayesian inverse problems with decoupled diffusion sequential monte carlo

Reference 80

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Observation ed09b81c-0f29-468d-845e-4fff3d631884 · outbound

This paper cites Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation.

Provable Diffusion Posterior Sampling for Bayesian Inversion Soft truncation: A universal training technique of score-based diffusion model for high precision score estimation

Reference 81

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This paper cites Test-time alignment of diffusion models without reward over-optimization.

Provable Diffusion Posterior Sampling for Bayesian Inversion Test-time alignment of diffusion models without reward over-optimization

Reference 82

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Provable Diffusion Posterior Sampling for Bayesian Inversion Auto-Encoding Variational Bayes

Reference 83

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This paper cites On the rate of convergence of fully connected deep neural network regression estimates.

Provable Diffusion Posterior Sampling for Bayesian Inversion On the rate of convergence of fully connected deep neural network regression estimates

Reference 84

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This paper cites Non-asymptotic error bounds for probability flow odes under weak log-concavity, 2025.

Provable Diffusion Posterior Sampling for Bayesian Inversion Non-asymptotic error bounds for probability flow odes under weak log-concavity, 2025

Reference 85

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Observation 91e0f94a-b4a6-4af6-94b7-2e0766fead30 · outbound

This paper cites Score-based generative modeling secretly minimizes the wasserstein distance.

Provable Diffusion Posterior Sampling for Bayesian Inversion Score-based generative modeling secretly minimizes the wasserstein distance

Reference 86

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This paper cites Deep laplacian pyramid networks for fast and accurate super-resolution.

Provable Diffusion Posterior Sampling for Bayesian Inversion Deep laplacian pyramid networks for fast and accurate super-resolution

Reference 87

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This paper cites On the well-posedness of bayesian inverse problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion On the well-posedness of bayesian inverse problems

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-03T17:55:18.111313Z

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Observation 6e9f22a6-79fa-40b8-b579-8b4490881292 · outbound

This paper cites Bayesian imaging using plug & play priors: when langevin meets tweedie.

Provable Diffusion Posterior Sampling for Bayesian Inversion Bayesian imaging using plug & play priors: when langevin meets tweedie

Reference 89

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This paper cites Concentration of measure and logarithmic S obolev inequalities.

Provable Diffusion Posterior Sampling for Bayesian Inversion Concentration of measure and logarithmic S obolev inequalities

Reference 90

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This paper cites Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo.

Provable Diffusion Posterior Sampling for Bayesian Inversion Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo

Reference 91

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This paper cites Convergence of score-based generative modeling for general data distributions.

Provable Diffusion Posterior Sampling for Bayesian Inversion Convergence of score-based generative modeling for general data distributions

Reference 92

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This paper cites Structured logconcave sampling with a restricted gaussian oracle.

Provable Diffusion Posterior Sampling for Bayesian Inversion Structured logconcave sampling with a restricted gaussian oracle

Reference 93

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This paper cites Accelerating Convergence of Score-Based Diffusion Models, Provably.

Provable Diffusion Posterior Sampling for Bayesian Inversion Accelerating Convergence of Score-Based Diffusion Models, Provably

Reference 94

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This paper cites Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models.

Provable Diffusion Posterior Sampling for Bayesian Inversion Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models

Reference 95

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Observation bdaf88d0-11b2-4cd4-861c-e16dd50597b0 · outbound

This paper cites Efficient Diffusion Posterior Sampling for Noisy Inverse Problems.

Provable Diffusion Posterior Sampling for Bayesian Inversion Efficient Diffusion Posterior Sampling for Noisy Inverse Problems

Reference 96

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Observation 37a3acad-350f-4a25-9939-d8ff5fcd99b3 · outbound

This paper cites Optimal transport-based generative models for bayesian posterior sampling, 2025 a.

Provable Diffusion Posterior Sampling for Bayesian Inversion Optimal transport-based generative models for bayesian posterior sampling, 2025 a

Reference 97

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This paper cites State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics.

Provable Diffusion Posterior Sampling for Bayesian Inversion State-observation augmented diffusion model for nonlinear assimilation with unknown dynamics

Reference 98

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This paper cites Physics-informed neural operator for learning partial differential equations.

Provable Diffusion Posterior Sampling for Bayesian Inversion Physics-informed neural operator for learning partial differential equations

Reference 99

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Provable Diffusion Posterior Sampling for Bayesian Inversion Unresolved cited work

Reference 100

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Pith citing papers

Observation c9c5af7d-4c63-43f5-ad51-06cfefcfb525 · inbound

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions cites this paper.

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions Provable Diffusion Posterior Sampling for Bayesian Inversion

Reference 2

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Observation 28ee4367-796a-43d9-9941-e2b5060eccb3 · inbound

Proximal-Based Generative Modeling for Bayesian Inverse Problems cites this paper.

Proximal-Based Generative Modeling for Bayesian Inverse Problems Provable Diffusion Posterior Sampling for Bayesian Inversion

Reference 81

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Observation 43da30e8-3ff1-41d1-a9c5-f801936d4526 · inbound

Image Restoration via Diffusion Models with Dynamic Resolution cites this paper.

Image Restoration via Diffusion Models with Dynamic Resolution Provable Diffusion Posterior Sampling for Bayesian Inversion

Reference 2

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Observation 988ff15d-30d5-4471-833d-8c1d9fed2546 · inbound

Tracing the Oracle: Improving Diffusion Timestep Scheduling for 3D CT Reconstruction cites this paper.

Tracing the Oracle: Improving Diffusion Timestep Scheduling for 3D CT Reconstruction Provable Diffusion Posterior Sampling for Bayesian Inversion

Reference 19

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