Paper Citation Record · LEDGER

Towards joint graph learning and sampling set selection from data

As of 23 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2412.09753.

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

pith.paper-citation-record.v1
2412.09753 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:50:49.181774Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

24 of 24 outbound references displayed

verified exact1
verified fuzzy20
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af56cf50-68de-484b-bfc7-36103bafb111 · outbound

This paper cites important.

Towards joint graph learning and sampling set selection from data important

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.547813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 55439a9e-73dc-4082-8e00-6df23ce675c4 · outbound

This paper cites an unresolved cited work.

Towards joint graph learning and sampling set selection from data Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-11T16:50:49.533611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3b065304-6569-44fa-bd38-ea6851eacd1a · outbound

This paper cites L or L + Q).

Towards joint graph learning and sampling set selection from data L or L + Q)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.518934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 170d0e07-d06a-4942-a1c5-1fdbf8e3ad15 · outbound

This paper cites informative.

Towards joint graph learning and sampling set selection from data informative

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.504595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 57b180a6-2e58-468f-a5a8-91e79981dda7 · outbound

This paper cites These node locations are ﬁxed across all ex- periments.

Towards joint graph learning and sampling set selection from data These node locations are ﬁxed across all ex- periments

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.490901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6ecbeb08-d86a-48d1-bebc-af522ce29016 · outbound

This paper cites We generate M = 100 random signals, each drawn from mul- tivariate Gaussian distribution fk ∼N (0, S), and add noise n∼ N (0, σ2 nI), where σn is the noise level.

Towards joint graph learning and sampling set selection from data We generate M = 100 random signals, each drawn from mul- tivariate Gaussian distribution fk ∼N (0, S), and add noise n∼ N (0, σ2 nI), where σn is the noise level

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.477012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3358ecc9-3b3b-4f08-999e-83fb64ad8537 · outbound

This paper cites an unresolved cited work.

Towards joint graph learning and sampling set selection from data Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-11T16:50:49.463058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 028d7d5e-5078-4424-b2e5-1d533fa511ba · outbound

This paper cites an unresolved cited work.

Towards joint graph learning and sampling set selection from data Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-11T16:50:49.449885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f9f6853d-46f0-4f8e-8e24-de83d2255845 · outbound

This paper cites Discrete signal processing on graphs: Sampl ing theory,.

Towards joint graph learning and sampling set selection from data Discrete signal processing on graphs: Sampl ing theory,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.436086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e20262a0-8665-410f-9a48-d06ac2121fd0 · outbound

This paper cites Sig- nal processing techniques for interpolation in graph struc tured data,.

Towards joint graph learning and sampling set selection from data Sig- nal processing techniques for interpolation in graph struc tured data,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.422575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 213c573e-22e4-4bca-9db6-b3ea154a1d4f · outbound

This paper cites Efﬁcient sampling set selection for bandlimited graph signals using graph spectral proxies,.

Towards joint graph learning and sampling set selection from data Efﬁcient sampling set selection for bandlimited graph signals using graph spectral proxies,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.408903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1f972ce2-493f-4204-85c3-ea54e0b74251 · outbound

This paper cites Practical graph s ignal sampling with log-linear size scaling,.

Towards joint graph learning and sampling set selection from data Practical graph s ignal sampling with log-linear size scaling,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.394819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation eea03908-c3a1-4bd3-ba05-9aedbf14b1ab · outbound

This paper cites Fast graph sampling set selection using gersh- gorin disc alignment,.

Towards joint graph learning and sampling set selection from data Fast graph sampling set selection using gersh- gorin disc alignment,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.381170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cca09602-f0c6-4ed4-b129-fa99c83d3167 · outbound

This paper cites Learning graphs from data: A signal representat ion perspective,.

Towards joint graph learning and sampling set selection from data Learning graphs from data: A signal representat ion perspective,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.367337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c591bb0a-b5ce-42b9-8f9a-a86774b5ff31 · outbound

This paper cites Gr aph learning from data under laplacian and structural constrai nts,.

Towards joint graph learning and sampling set selection from data Gr aph learning from data under laplacian and structural constrai nts,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.353281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fdd2666f-649f-43c0-8218-d16a8f16266f · outbound

This paper cites An efﬁcient algorith m for graph laplacian optimization based on effective resistanc es,.

Towards joint graph learning and sampling set selection from data An efﬁcient algorith m for graph laplacian optimization based on effective resistanc es,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.338661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2d42e3a-9378-4023-8a7a-3a3115ba8d0c · outbound

This paper cites Joint graph and vertex importance learning,.

Towards joint graph learning and sampling set selection from data Joint graph and vertex importance learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.323771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 09a1bac7-6227-4355-95f8-e3ba509d0be0 · outbound

This paper cites Irregularity-aware graph fourier transforms ,.

Towards joint graph learning and sampling set selection from data Irregularity-aware graph fourier transforms ,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.309620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ac628aa3-b4ea-4730-ae3d-73218a58f667 · outbound

This paper cites A probabilistic inte rpre- tation of sampling theory of graph signals,.

Towards joint graph learning and sampling set selection from data A probabilistic inte rpre- tation of sampling theory of graph signals,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.294467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 84b2e96f-bdef-4cab-bbda-546db7fe8e4d · outbound

This paper cites Graph-based Scalable Sampling of 3D Point Cloud Attributes.

Towards joint graph learning and sampling set selection from data Graph-based Scalable Sampling of 3D Point Cloud Attributes

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-11T16:50:49.223172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4eb3a5ef-513f-48dd-b696-1e88ee4dbdda · outbound

This paper cites Near - optimal sensor placements in gaussian processes: Theory, e f- ﬁcient algorithms and empirical studies.,.

Towards joint graph learning and sampling set selection from data Near - optimal sensor placements in gaussian processes: Theory, e f- ﬁcient algorithms and empirical studies.,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.280079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fde3bb18-9bc5-4ae1-a308-802fcbc8c9cd · outbound

This paper cites Horn and Charles R.

Towards joint graph learning and sampling set selection from data Horn and Charles R

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.266307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 564d0bcf-4810-4c2b-a001-767a1d748cff · outbound

This paper cites Eigendecomposition-free sampling set selection for graph signals,.

Towards joint graph learning and sampling set selection from data Eigendecomposition-free sampling set selection for graph signals,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.252251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc47204a-582f-4d3f-9e1b-02217d9eb500 · outbound

This paper cites A distance-base d for- mulation for sampling signals on graphs,.

Towards joint graph learning and sampling set selection from data A distance-base d for- mulation for sampling signals on graphs,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T16:50:49.237934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.