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Paper Citation Record · LEDGER

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference

As of 13 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2411.13625.

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

pith.paper-citation-record.v1
2411.13625 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:42:22.136655Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:29:10.551078Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T21:29:11.100423Z

Reference resolution

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0fdcc20-bd61-471c-8709-92fdf850627d · outbound

This paper cites an unresolved cited work.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Unresolved cited work

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 313bb011-19cb-4f7d-b98a-84ec290bae46 · outbound

This paper cites Jeffreys , journal Proceedings of the Royal Society of London.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Jeffreys , journal Proceedings of the Royal Society of London

Reference 2

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Observation 95673d85-7a8e-4ab7-94d0-dfe4a17bcba0 · outbound

This paper cites Jeffreys , title Theory of Probability ( publisher Oxford University Press , address Oxford, England , year 1948 ), edition second edition ed.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Jeffreys , title Theory of Probability ( publisher Oxford University Press , address Oxford, England , year 1948 ), edition second edition ed

Reference 3

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Source-reported events for the cited work

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Observation 634f9043-10bd-4651-93a8-d5516b59629f · outbound

This paper cites Amari , title Information Geometry and Its Applications , vol.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Amari , title Information Geometry and Its Applications , vol

Reference 4

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Observation eb8fca18-ccf1-4f88-81be-7dea530b2f84 · outbound

This paper cites Kirkpatrick , author C.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Kirkpatrick , author C

Reference 5

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Observation 51e259da-aced-4987-bd66-2e3c90df8363 · outbound

This paper cites Lewis and author S.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Lewis and author S

Reference 6

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Observation 667f78a0-0202-4c2c-89a5-08f41f07f5af · outbound

This paper cites o ver , author L. C. Bartels , and author B. M. Sch \.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference o ver , author L. C. Bartels , and author B. M. Sch \

Reference 7

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Source-reported events for the cited work

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Observation 067e209c-a68c-484b-bdfe-592325c0a0f9 · outbound

This paper cites Bayesian distances for quantifying tensions in cosmological inference and the surprise statistic.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Bayesian distances for quantifying tensions in cosmological inference and the surprise statistic

Reference 8

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Source-reported events for the cited work

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Observation 1cd78838-7e34-4c4a-b4f4-2cb77964071d · outbound

This paper cites Jarzynski , journal Phys.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Jarzynski , journal Phys

Reference 9

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Observation 4875d99c-36d1-4fe7-90e1-492564d7db75 · outbound

This paper cites an unresolved cited work.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Unresolved cited work

Reference 10

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Observation 2561569d-1aa1-4f4e-84dd-5fa2fb37ac6f · outbound

This paper cites an unresolved cited work.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Unresolved cited work

Reference 11

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Observation b3d946b4-0857-4956-b564-dc112c38b898 · outbound

This paper cites Schosser , author T.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Schosser , author T

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 13275533-d7ac-46b1-8ebb-5bd1d57a498c · outbound

This paper cites Partition function approach to non-Gaussian likelihoods: macrocanonical partitions and replicating Markov-chains.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Partition function approach to non-Gaussian likelihoods: macrocanonical partitions and replicating Markov-chains

Reference 13

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Observation fdf915a0-e93f-442b-987c-06d0b5dbbb32 · outbound

This paper cites Renyi Entropy and Free Energy.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Renyi Entropy and Free Energy

Reference 14

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This paper cites Harremo \"e s , journal Physica A: Statistical Mechanics and its Applications volume 365 , pages 57 ( year 2006 ), ISSN issn 0378-4371 , ://dx.doi.org/10.1016/j.physa.2006.01.012.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Harremo \"e s , journal Physica A: Statistical Mechanics and its Applications volume 365 , pages 57 ( year 2006 ), ISSN issn 0378-4371 , ://dx.doi.org/10.1016/j.physa.2006.01.012

Reference 15

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Observation 05e4b358-a3e2-4526-871d-4fbbf016e34a · outbound

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Unresolved cited work

Reference 16

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Observation cba073c3-17a6-4fa0-9410-dad810f6d7dd · outbound

This paper cites R\'enyi Divergence and Kullback-Leibler Divergence.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference R\'enyi Divergence and Kullback-Leibler Divergence

Reference 17

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Observation e731c7a0-e740-412f-947b-75dec80f0b72 · outbound

This paper cites A Bayesian Characterization of Relative Entropy.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference A Bayesian Characterization of Relative Entropy

Reference 18

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Observation f42bc8fd-5512-40b8-9ba9-2b50149dba95 · outbound

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Information geometry in cosmological inference problems

Reference 19

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Unresolved cited work

Reference 20

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Observation bb745910-e1f2-46af-b6dd-733b3f7d9c2d · outbound

This paper cites Supernova cosmology: legacy and future.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Supernova cosmology: legacy and future

Reference 21

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Observation 785be284-fd11-4a87-ab1d-5f1e83ba86aa · outbound

This paper cites Constructing Exact Confidence Regions on Parameter Manifolds of Non-Linear Models.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Constructing Exact Confidence Regions on Parameter Manifolds of Non-Linear Models

Reference 22

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Observation a543f40f-e1e7-4048-99af-090365a3af82 · outbound

This paper cites Suzuki , author D.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Suzuki , author D

Reference 23

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Kowalski , author D

Reference 24

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Amanullah , author C

Reference 25

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Observation cfb7d27d-8281-4564-854f-c543da172dd0 · outbound

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference emcee: The MCMC Hammer

Reference 26

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Observation 1de21614-f0b1-415c-b850-23d2d80ff4c9 · outbound

This paper cites X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference X-ray spectral modelling of the AGN obscuring region in the CDFS: Bayesian model selection and catalogue

Reference 27

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Observation ec9caee4-895c-46aa-9903-57ff65bd187e · outbound

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Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference Feroz , author M

Reference 28

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Observation 1469a19c-28bc-4926-953e-832979bef1f4 · outbound

This paper cites o spel , author A. Schlosser , and author B. M. Sch \.

Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference o spel , author A. Schlosser , and author B. M. Sch \

Reference 29

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Source-reported events for the cited work

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Pith citing papers

Observation e569fce2-4d03-48ba-b3dd-b948f97929cb · inbound

Approximating non-Gaussian Bayesian partitions with normalising flows: statistics, inference and application to cosmology cites this paper.

Approximating non-Gaussian Bayesian partitions with normalising flows: statistics, inference and application to cosmology Partition function approach to non-Gaussian likelihoods: information theory and state variables for Bayesian inference

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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