Paper Citation Record · LEDGER

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing

As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2606.31230.

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

pith.paper-citation-record.v1
2606.31230 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-01T06:35:07.063743Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:19:35.738370Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

verified exact2
verified fuzzy39
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38147c21-dc35-4720-9081-d2e58349d8c6 · outbound

This paper cites Better Models and Algorithms for Learning Ising Models from Dynamics.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Better Models and Algorithms for Learning Ising Models from Dynamics

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:35:29.305811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dcf7d572-28eb-40cb-925f-5ea2b763596e · outbound

This paper cites Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Proceedings of the 2026 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA) , pages=

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.431905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e5cbb5c7-7a79-4487-a6f6-3b216354d535 · outbound

This paper cites Frontiers in psychology , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Frontiers in psychology , volume=

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.434879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7ebca3d2-28f5-44fe-927f-1f041ec3ec4f · outbound

This paper cites Expert systems with applications , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Expert systems with applications , volume=

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.437255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b3e1d7f4-b76f-4e18-9193-75f76214f061 · outbound

This paper cites Proceedings of the 56th Annual ACM Symposium on Theory of Computing , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Proceedings of the 56th Annual ACM Symposium on Theory of Computing , pages=

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.442635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a1395c69-b7ce-415f-8aed-774d059a96cb · outbound

This paper cites Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.448286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d650ce38-1614-45b2-b517-9014f816e01a · outbound

This paper cites Journal of Multivariate Analysis , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Journal of Multivariate Analysis , volume=

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.445403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 99bf28cc-0434-468e-8817-792dc0d65648 · outbound

This paper cites SIAM journal on computing , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing SIAM journal on computing , volume=

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.413209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation be46b0c1-141f-4f4a-bd17-876c3b570364 · outbound

This paper cites Conference on Learning Theory , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Conference on Learning Theory , pages=

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.409655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 325748e1-5922-4085-a2dc-6b65d32597f1 · outbound

This paper cites Chaos: An Interdisciplinary Journal of Nonlinear Science , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Chaos: An Interdisciplinary Journal of Nonlinear Science , volume=

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.478457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f92e68c3-d52b-4421-8f5b-64fe909ddc15 · outbound

This paper cites NeuroImage , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing NeuroImage , volume=

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.416698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b21dda09-50b6-491a-bd29-0c0a3efc58ba · outbound

This paper cites Frontiers in aging neuroscience , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Frontiers in aging neuroscience , volume=

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.406027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 399c047e-6f0b-41ba-8efc-795f7312f759 · outbound

This paper cites BMC systems biology , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing BMC systems biology , volume=

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.407702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c4d19883-39eb-44c3-95c3-28f00b52171e · outbound

This paper cites Biometrics , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Biometrics , volume=

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.465797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4ff71193-b022-4321-ab53-105f46e77279 · outbound

This paper cites 2023 , publisher=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2023 , publisher=

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.418292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 19a64c96-c63c-4ffe-aa94-2ec882aaf378 · outbound

This paper cites The Thirty Seventh Annual Conference on Learning Theory , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing The Thirty Seventh Annual Conference on Learning Theory , pages=

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.440322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0a8eadc6-f998-4ade-ab50-b548b3f7a867 · outbound

This paper cites The Thirty Seventh Annual Conference on Learning Theory , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing The Thirty Seventh Annual Conference on Learning Theory , pages=

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.404173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 24309cc4-8517-4244-a2db-f212374e25d9 · outbound

This paper cites Proceedings of the 57th Annual ACM Symposium on Theory of Computing , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Proceedings of the 57th Annual ACM Symposium on Theory of Computing , pages=

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.400891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ac0336d0-63f7-4983-829e-7cb60219d3ce · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Advances in Neural Information Processing Systems , volume=

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.402554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5890c71e-b62f-42e7-928e-eb2e9fe8e685 · outbound

This paper cites Conference on Learning Theory , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Conference on Learning Theory , pages=

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.411443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c75ac945-65ff-40c1-996f-6cf22137144d · outbound

This paper cites IEEE Transactions on Information Theory , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing IEEE Transactions on Information Theory , volume=

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.393553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ff5b86d0-7c51-4650-932c-ffd30ea6a7b3 · outbound

This paper cites 2010 IEEE International Symposium on Information Theory , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2010 IEEE International Symposium on Information Theory , pages=

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.397202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3fec2c77-5a74-4830-9626-a7d72b77c9db · outbound

This paper cites 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS) , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS) , pages=

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.399120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a4efafc3-616c-4cad-ba7d-e4c52f2dc490 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Advances in Neural Information Processing Systems , volume=

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.395334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b028eab-0c15-4d77-b33e-73353d5878ca · outbound

This paper cites International conference on machine learning , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing International conference on machine learning , pages=

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.458354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cee01549-763d-4f13-ba0d-c6142f4ec1c3 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Advances in Neural Information Processing Systems , volume=

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.425399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 525b5af4-b81d-498a-9edf-3531ddb7648c · outbound

This paper cites Annals of Statistics , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Annals of Statistics , volume=

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.483582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7b7c390c-333c-4f79-b6ef-258f48f89cdd · outbound

This paper cites Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T06:35:29.310716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8b1f91f0-1d69-43b8-9435-c71cd6cb8619 · outbound

This paper cites 2019 , publisher=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2019 , publisher=

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.473855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 03cb3220-77b9-4076-acb9-e4efea7083d5 · outbound

This paper cites 2017 , publisher=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2017 , publisher=

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.475814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c9b98fa-ff66-4201-8056-8f9c719f1842 · outbound

This paper cites 2025 IEEE International Symposium on Information Theory (ISIT) , pages=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2025 IEEE International Symposium on Information Theory (ISIT) , pages=

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.481011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b781729b-bfee-43ad-b9d5-d8a3ffeb09a4 · outbound

This paper cites The Annals of Statistics , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing The Annals of Statistics , volume=

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.471783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6c4724a5-f387-4b8d-94be-af6770ee4e1c · outbound

This paper cites SODA 2019 , year=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing SODA 2019 , year=

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.469338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f7aefafb-a8b1-4b55-b5aa-6824723cc4da · outbound

This paper cites 2009 , publisher =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing 2009 , publisher =

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.486945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation ab1a331a-9fc1-43ea-9f59-d0d0b48b2bff · outbound

This paper cites Journal of the Royal Statistical Society: Series B (Methodological) , volume =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Journal of the Royal Statistical Society: Series B (Methodological) , volume =

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.460834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 773c7855-c8a1-4eda-a420-13707ad84cda · outbound

This paper cites Annals of Statistics , volume =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Annals of Statistics , volume =

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.415038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation be17d3b1-645a-4fda-a8d5-3520ffe9f3c6 · outbound

This paper cites Annals of Statistics , volume =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Annals of Statistics , volume =

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.420036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d644a844-9b45-4f61-844e-654796f1d83d · outbound

This paper cites and Raskutti, Garvesh and Yu, Bin , journal =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing and Raskutti, Garvesh and Yu, Bin , journal =

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.463042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 40831677-e83c-4dc7-a531-65e59fdd5755 · outbound

This paper cites , title =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing , title =

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.451776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 05b32031-18f3-44c2-973a-35a565dfb3aa · outbound

This paper cites , year =.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing , year =

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.455467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 725eabb2-0dbc-4a92-bf00-97e62053cb3e · outbound

This paper cites Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing Locally Stationary Distributions: A Framework for Analyzing Slow-Mixing Markov Chains

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-07-01T06:35:29.315262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4a1fb64e-bbaa-4963-8ba0-f80e88cb9fe7 · outbound

This paper cites IEEE Transactions on Information Theory , volume=.

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing IEEE Transactions on Information Theory , volume=

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-06T17:52:45.428184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation fc454184-f8ab-4de1-94b8-a7c238aa626a · inbound

Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics cites this paper.

Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T15:19:35.738370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.