Paper Citation Record · LEDGER

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks

As of 23 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:1908.05835.

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

pith.paper-citation-record.v1
1908.05835 v4

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:11:33.795444Z

measured 35 of 35 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

35 of 35 outbound references displayed

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verified fuzzy34
unresolved1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 90a85f6b-1443-4ce2-a5ea-61ef5b055b0c · outbound

This paper cites Estima tion of Spatially Correlated Random Fields in Heterogeneous Wireless Sensor Networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Estima tion of Spatially Correlated Random Fields in Heterogeneous Wireless Sensor Networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:35.119467Z

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 e83caa07-94f5-451d-9b96-4c9fc9b7e039 · outbound

This paper cites Optimal multi-type s ensor placements in gaussian spatial ﬁelds for environmental monitoring,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Optimal multi-type s ensor placements in gaussian spatial ﬁelds for environmental monitoring,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:35.074939Z

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 ae4651b4-ba92-4e20-b4f8-99fcdf995332 · outbound

This paper cites Short-ter m solar power forecasting based on weighted gaussian process regression,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Short-ter m solar power forecasting based on weighted gaussian process regression,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:35.046991Z

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 61d1422f-1463-4650-b92a-8f96f4347547 · outbound

This paper cites Sohraby , D.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Sohraby , D

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:35.003166Z

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 32242c8d-04af-4678-873d-f5cd292b3626 · outbound

This paper cites De centralized hypothesis testing in wireless sensor networks in the presence of misbehaving nodes,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks De centralized hypothesis testing in wireless sensor networks in the presence of misbehaving nodes,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.951071Z

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 3bfc4b45-51da-4d1a-8785-6fe5fa286727 · outbound

This paper cites Calibration of mul ti-target tracking algorithms using non-cooperative targets,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Calibration of mul ti-target tracking algorithms using non-cooperative targets,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.900836Z

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 16b49fcb-1141-43e9-8023-6e8cb9b7f02e · outbound

This paper cites Draft roadmap for next generation air monit oring,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Draft roadmap for next generation air monit oring,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.860891Z

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 0559f0b7-ebba-40d6-bd83-ed3fba8de110 · outbound

This paper cites Model-based ren dezvous calibration of mobile sensor networks for monitoring air quality ,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Model-based ren dezvous calibration of mobile sensor networks for monitoring air quality ,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.833534Z

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 96f3b51d-7f8f-4366-aefd-302bc21e6c06 · outbound

This paper cites Random access sen sor networks: Field reconstruction from incomplete data,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Random access sen sor networks: Field reconstruction from incomplete data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.795961Z

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 f06d260a-1ae1-4b08-aa7e-e8a01892a67a · outbound

This paper cites Quality of information in mobile crowdsensing: Survey and research challenges,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Quality of information in mobile crowdsensing: Survey and research challenges,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.758272Z

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 0a1b27bd-7ce4-4a56-8b34-d3ea75732f61 · outbound

This paper cites Using multi-parameters for calibr ation of low-cost sensors in urban environment,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Using multi-parameters for calibr ation of low-cost sensors in urban environment,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.729068Z

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 e0c1456d-15b7-4446-8c9d-fa72f776ca0a · outbound

This paper cites Possible artifacts of data biases in the recen t global surface warming hiatus,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Possible artifacts of data biases in the recen t global surface warming hiatus,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.704814Z

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 7fccc67b-a261-4da7-aaf2-152a25de2712 · outbound

This paper cites Convex o ptimization approaches for blind sensor calibration using sparsity ,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Convex o ptimization approaches for blind sensor calibration using sparsity ,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.677622Z

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 7e1d7ef5-a329-42b7-b820-401c1e4a009a · outbound

This paper cites On re ndezvous in mobile sensing networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks On re ndezvous in mobile sensing networks,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.615910Z

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 f36efda4-b7a2-4ca9-bbc5-79e9eb278dff · outbound

This paper cites Info rmed nonnegative matrix factorization methods for mobile sensor network calibration,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Info rmed nonnegative matrix factorization methods for mobile sensor network calibration,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.553322Z

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 08b62531-b836-413e-b55a-99f886806963 · outbound

This paper cites Sensor calibration fo r off-the-grid spectral estimation,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Sensor calibration fo r off-the-grid spectral estimation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.494995Z

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 30f35d07-b245-459f-9ec2-7e41294f985a · outbound

This paper cites A non-convex approach to joi nt sensor calibration and spectrum estimation,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks A non-convex approach to joi nt sensor calibration and spectrum estimation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.472063Z

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 b491d421-d2ed-4310-9bac-91cdb593a96e · outbound

This paper cites A secure opti mum distributed detection scheme in under-attack wireless sensor networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks A secure opti mum distributed detection scheme in under-attack wireless sensor networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.431953Z

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 1aac07da-1607-4823-80ed-1a33332bd6d1 · outbound

This paper cites Collaborative spectrum sensing in the presence of byzantine attacks in cognitive radio networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Collaborative spectrum sensing in the presence of byzantine attacks in cognitive radio networks,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.403547Z

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 889ccf02-7295-47bc-871c-09495bbc3888 · outbound

This paper cites Distributed ev ent detection under byzantine attack in wireless sensor 40 networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Distributed ev ent detection under byzantine attack in wireless sensor 40 networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.374131Z

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 f9672c1e-9897-4d53-9ec8-8489925afa21 · outbound

This paper cites Crowdsourcing urban survei llance: The development of homeland security markets for environmental sensor networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Crowdsourcing urban survei llance: The development of homeland security markets for environmental sensor networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.343226Z

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 4277cc43-1e6e-4f26-abdf-fad58268b0e3 · outbound

This paper cites Crowd-based learning of spatial ﬁelds for the internet of things: From harvesting of data to inference,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Crowd-based learning of spatial ﬁelds for the internet of things: From harvesting of data to inference,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.306049Z

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 3d33b368-94ef-4f7c-831b-971e7daa5325 · outbound

This paper cites Spatial ﬁeld reconstruction and sensor selection in heterogeneous sensor networks with stochastic energy ha rvesting,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Spatial ﬁeld reconstruction and sensor selection in heterogeneous sensor networks with stochastic energy ha rvesting,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.266564Z

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 eb793c1c-9b89-404e-b00d-cd333a81e706 · outbound

This paper cites How to Utilize Sen sor Network Data to Efﬁciently Perform Model Calibration and Spatial Field Reconstruction,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks How to Utilize Sen sor Network Data to Efﬁciently Perform Model Calibration and Spatial Field Reconstruction,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.235576Z

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 8580242b-3ed1-4838-a58d-34fd34958b12 · outbound

This paper cites Random Field Reconstruction With Quantization in Wireless Sensor Networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Random Field Reconstruction With Quantization in Wireless Sensor Networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.202472Z

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 6b0b6b1d-c5e4-4630-bb7f-3798cec79c9b · outbound

This paper cites Sampling and reconst ruction of spatial ﬁelds using mobile sensors,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Sampling and reconst ruction of spatial ﬁelds using mobile sensors,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.174157Z

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 71d98bdc-043e-489f-ae1f-a57fc13bdad8 · outbound

This paper cites Estimating spatial averages of envi ronmental parameters based on mobile crowdsensing,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Estimating spatial averages of envi ronmental parameters based on mobile crowdsensing,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.148339Z

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 eba3b125-bf27-4871-b440-f865e17985fd · outbound

This paper cites A trust-base d mixture of gaussian processes model for reliable regression in participatory sensing.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks A trust-base d mixture of gaussian processes model for reliable regression in participatory sensing

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.112315Z

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 1d502920-0566-4651-9983-6aa8e84dff57 · outbound

This paper cites Location-aw are cooperative spectrum sensing via Gaussian Processes,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Location-aw are cooperative spectrum sensing via Gaussian Processes,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:34.084439Z

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 b98075bc-ffcd-4402-ae8c-bbd7b0d3c31e · outbound

This paper cites an unresolved cited work.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-14T13:11:34.051390Z

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 539b5eff-6637-4edf-9288-498dc200c459 · outbound

This paper cites Calibree: A self-calibration system for mobile sensor networks,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Calibree: A self-calibration system for mobile sensor networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:33.998400Z

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 2a0f2fde-e3e7-40be-b7c1-b252203794b0 · outbound

This paper cites The cross-entropy method for combinat orial and continuous optimization,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks The cross-entropy method for combinat orial and continuous optimization,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:33.961586Z

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 211b4536-cc4a-4cc2-8540-2a8598c589dc · outbound

This paper cites A gentle tutorial of the em algorithm and its application t o parameter estimation for gaussian mixture and hidden markov models,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks A gentle tutorial of the em algorithm and its application t o parameter estimation for gaussian mixture and hidden markov models,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:33.934826Z

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 7a59956f-bdaf-435b-ad5d-6cc3b3a9e31e · outbound

This paper cites On the statistical analysis of dirty picture s,.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks On the statistical analysis of dirty picture s,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:33.898794Z

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 ffe39c9e-9739-4f39-8f08-6c5028352c37 · outbound

This paper cites Friedman, T.

Bayesian Spatial Field Reconstruction with Unknown Distortions in Sensor Networks Friedman, T

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:11:33.866416Z

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.