Paper Citation Record · LEDGER

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2603.23196.

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pith.paper-citation-record.v1
2603.23196 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T19:47:15.974727Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:32:05.581160Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T08:45:57.600878Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation 84f03f43-70ce-4d99-9a05-973b53aa1a42 · outbound

This paper cites Theζ(2) limit in the random assignment problem.Random Structures & Algorithms, 18(4):381–418, 2001.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Theζ(2) limit in the random assignment problem.Random Structures & Algorithms, 18(4):381–418, 2001

Reference 1

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Observation bb065048-8ad3-4e5a-a846-8fae0782332c · outbound

This paper cites Bakry, I.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Bakry, I

Reference 2

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Observation 36ffb2a8-b129-4e30-854c-0534a7712169 · outbound

This paper cites Functional inequalities for Gaussian convolutions of compactly supported mea- sures: Explicit bounds and dimension dependence.Bernoulli, 24(1):333 – 353, 2018.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Functional inequalities for Gaussian convolutions of compactly supported mea- sures: Explicit bounds and dimension dependence.Bernoulli, 24(1):333 – 353, 2018

Reference 3

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Observation 8849d833-0b8c-4727-bab1-83a6dcc9cd5e · outbound

This paper cites Springer, 2006.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Springer, 2006

Reference 4

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Observation 68d256b1-de75-4cd1-a7d0-8b153d3122dd · outbound

This paper cites Computer-assisted analysis of mixtures and applications, 2000.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Computer-assisted analysis of mixtures and applications, 2000

Reference 5

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Observation df33c58a-6194-4b23-a2d3-a4ebdc221234 · outbound

This paper cites Boucheron, G.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Boucheron, G

Reference 6

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Observation ac3b36a3-f84d-4fe5-8000-3f9e7bf0415e · outbound

This paper cites Oxford University Press, 02 2013.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Oxford University Press, 02 2013

Reference 7

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Observation fbb8439f-44ae-4344-96ce-2f8de4af49af · outbound

This paper cites Springer, 2014.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Springer, 2014

Reference 8

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Observation f84e0062-25d6-4527-9bba-7163ef1c4ed0 · outbound

This paper cites Consistency of the mle under mixture models.Statistical Science, 32(1):47–63, 2017.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Consistency of the mle under mixture models.Statistical Science, 32(1):47–63, 2017

Reference 9

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Observation edc09536-4fa0-411f-aa14-1a5f70db189a · outbound

This paper cites Maximum likelihood from incomplete data via the em algorithm.Journal of the royal statistical society: series B (methodological), 39(1):1–22, 1977.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Maximum likelihood from incomplete data via the em algorithm.Journal of the royal statistical society: series B (methodological), 39(1):1–22, 1977

Reference 10

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Observation 9a6948d9-d45b-47a4-811e-4bbd49c03ef2 · outbound

This paper cites Springer Science & Business Media, 2013.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Springer Science & Business Media, 2013

Reference 11

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Observation d7e0fd82-dbf2-4aa9-ac9f-f002a989896e · outbound

This paper cites Fukushima, Y.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Fukushima, Y

Reference 12

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Observation ea5b66d3-5cc9-4e9f-9e9d-8b9340819084 · outbound

This paper cites Posterior convergence rates of dirichlet mixtures at smooth densities.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Posterior convergence rates of dirichlet mixtures at smooth densities

Reference 13

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Observation 79c127ce-b0b9-470d-b9aa-7fd544a2e527 · outbound

This paper cites General maximum likelihood empirical bayes estimation of normal means.The Annals of Statistics, 37(4):1647–1684, 2009.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics General maximum likelihood empirical bayes estimation of normal means.The Annals of Statistics, 37(4):1647–1684, 2009

Reference 14

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Observation 2b0735fa-1596-41cd-98a4-60fcbbd3d8be · outbound

This paper cites Consistency of the maximum likelihood esti- mator in the presence of infinitely many incidental parameters.The Annals of Mathematical Statistics, pages 887–906, 1956.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Consistency of the maximum likelihood esti- mator in the presence of infinitely many incidental parameters.The Annals of Mathematical Statistics, pages 887–906, 1956

Reference 15

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Observation af10d17d-dd29-409b-be78-8ee94dba12f9 · outbound

This paper cites Minimax bounds for estimation of normal mixtures.Bernoulli, pages 1802–1818, 2014.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Minimax bounds for estimation of normal mixtures.Bernoulli, pages 1802–1818, 2014

Reference 16

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Observation 86d7d8b6-5bf3-4946-9e42-858dbc84da57 · outbound

This paper cites Minimax bounds for estimat- ing multivariate gaussian location mixtures.Electronic Journal of Statistics, 16(1):1461–1484, 2022.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Minimax bounds for estimat- ing multivariate gaussian location mixtures.Electronic Journal of Statistics, 16(1):1461–1484, 2022

Reference 17

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Observation 2a4c9f46-b882-40ae-b34f-3d8bdef23df3 · outbound

This paper cites an unresolved cited work.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Unresolved cited work

Reference 18

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Observation 0e67d455-195b-424f-9aa4-649929cc8c0f · outbound

This paper cites Convex optimization, shape constraints, com- pound decisions, and empirical bayes rules.Journal of the American Statistical Association, 109(506):674–685, 2014.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Convex optimization, shape constraints, com- pound decisions, and empirical bayes rules.Journal of the American Statistical Association, 109(506):674–685, 2014

Reference 19

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Observation 6e14bd7e-6b51-4d04-8ee4-ec7e59af82f6 · outbound

This paper cites Number 89.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Number 89

Reference 20

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Observation 9b4629f3-8beb-4579-8b08-7934105fb025 · outbound

This paper cites Mixture models: theory, geometry, and applications.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Mixture models: theory, geometry, and applications

Reference 21

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Observation e662e0e6-e742-494f-804e-8b4c721e64ba · outbound

This paper cites Uniqueness of estimation and identifia- bility in mixture models.Canadian Journal of Statistics, 21(2):139–147, 1993.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Uniqueness of estimation and identifia- bility in mixture models.Canadian Journal of Statistics, 21(2):139–147, 1993

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-13T19:47:15.974727Z

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Observation c3f62aff-b366-45f6-88d1-4021dbb1607b · outbound

This paper cites On the best approximation by finite gaussian mixtures.IEEE Transactions on Information Theory, 2025.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics On the best approximation by finite gaussian mixtures.IEEE Transactions on Information Theory, 2025

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Observation 7411be49-d53a-46de-b663-5b5811c10752 · outbound

This paper cites Finite mixture models.Annual review of statistics and its application, 6(1):355–378, 2019.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Finite mixture models.Annual review of statistics and its application, 6(1):355–378, 2019

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-13T19:47:15.974727Z

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Observation 6cade4a5-4b7b-4d13-af39-2b29183b151b · outbound

This paper cites A conjecture on random bipartite matching.arXiv preprint cond- mat/9801176, 1998.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics A conjecture on random bipartite matching.arXiv preprint cond- mat/9801176, 1998

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Resolution: unresolved; no resolver link, observed 2026-07-13T19:47:15.974727Z

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Observation ee4948d3-6d7e-4860-936b-39fc5e1b7632 · outbound

This paper cites Consistency of maximum likelihood estimators for certain non- parametric families, in particular: mixtures.Journal of Statistical Planning and Inference, 19(2):137–158, 1988.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Consistency of maximum likelihood estimators for certain non- parametric families, in particular: mixtures.Journal of Statistical Planning and Inference, 19(2):137–158, 1988

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Observation b8de649d-7d26-42b3-9e7f-585169c12241 · outbound

This paper cites Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models

Reference 27

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Observation a411d379-c733-4e82-bb84-3cb35727ddca · outbound

This paper cites A generalization of the method of maximum likelihood- estimating a mixing distribution.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics A generalization of the method of maximum likelihood- estimating a mixing distribution

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Observation 0752b1c9-2dad-4154-bf28-18134557cf03 · outbound

This paper cites On the nonparametric maximum likelihood estimator for gaussian location mixture densities with application to gaussian denoising.The Annals of Statistics, 48(2):738–762, 2020.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics On the nonparametric maximum likelihood estimator for gaussian location mixture densities with application to gaussian denoising.The Annals of Statistics, 48(2):738–762, 2020

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Observation bc4e6dc0-5123-4b7b-a80c-964b604b0bfc · outbound

This paper cites Multivariate, heteroscedastic empirical bayes via nonparametric maximum likelihood.Journal of the Royal Statistical Society Series B: Statistical Methodology, 87(1):1–32, 05 2024.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Multivariate, heteroscedastic empirical bayes via nonparametric maximum likelihood.Journal of the Royal Statistical Society Series B: Statistical Methodology, 87(1):1–32, 05 2024

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Observation 8245d101-9ef6-43b5-8a29-386d84b0daab · outbound

This paper cites Finite mixture distributions., 1981.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Finite mixture distributions., 1981

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Observation 9a7f5ff3-f5ff-489b-a637-20d5a403aca8 · outbound

This paper cites Cambridge university press, 2000.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Cambridge university press, 2000

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Observation 9d6b5216-4a63-4001-a5cd-daa31d8ea365 · outbound

This paper cites Probability inequalities for likelihood ratios and convergence rates of sieve mles.The Annals of Statistics, pages 339– 362, 1995.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Probability inequalities for likelihood ratios and convergence rates of sieve mles.The Annals of Statistics, pages 339– 362, 1995

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Observation b3b4381a-7286-407e-b869-14f836992d07 · outbound

This paper cites Statistical physics of inference: Thresh- olds and algorithms.Advances in Physics, 65(5):453–552, 2016.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Statistical physics of inference: Thresh- olds and algorithms.Advances in Physics, 65(5):453–552, 2016

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Observation a78c1309-82b9-4bbe-8b76-484dd2038d9e · outbound

This paper cites Generalized maximum likelihood estimation of normal mixture densities.Statistica Sinica, pages 1297–1318, 2009.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Generalized maximum likelihood estimation of normal mixture densities.Statistica Sinica, pages 1297–1318, 2009

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Observation df71ebe6-be92-43e1-b5da-5ad5eabaee92 · outbound

This paper cites On efficient and scalable computation of the nonparametric maximum likelihood estimator in mixture models.Journal of Machine Learning Research, 25(8):1–46, 2024.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics On efficient and scalable computation of the nonparametric maximum likelihood estimator in mixture models.Journal of Machine Learning Research, 25(8):1–46, 2024

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Observation 3764cad4-7d12-49d2-93ab-71a2075bd4fa · outbound

This paper cites Deep autoencoding gaussian mixture model for unsuper- vised anomaly detection.

Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics Deep autoencoding gaussian mixture model for unsuper- vised anomaly detection

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Pith citing papers

Observation fb736d90-224a-453b-bca4-87a38f940492 · inbound

Characterisations of Kullback--Leibler approximation by finite Gaussian mixtures cites this paper.

Characterisations of Kullback--Leibler approximation by finite Gaussian mixtures Gaussian mixtures and non-parametric likelihoods through the lens of statistical mechanics

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-09T02:19:52.061709Z

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