Paper Citation Record · LEDGER

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models

As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2606.29862.

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

pith.paper-citation-record.v1
2606.29862 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T05:31:51.162101Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

43 of 43 outbound references displayed

verified exact3
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce261dbd-713f-4fc6-8e5e-0c35ea1e2600 · outbound

This paper cites Radial basis functions.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Radial basis functions

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91aabe22-3042-4ad8-9cbc-6921f4f9fcd6 · outbound

This paper cites Weight uncertainty in neural network.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Weight uncertainty in neural network

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f128aec-687e-4e75-be31-cfc57b7e5738 · outbound

This paper cites Estimating epistemic and aleatoric uncertainty with a single model.Advances in Neural Information Pro- cessing Systems, 37:109845–109870, 2024.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Estimating epistemic and aleatoric uncertainty with a single model.Advances in Neural Information Pro- cessing Systems, 37:109845–109870, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34d2da6c-1d62-4446-9456-743260f64a6f · outbound

This paper cites A graph neural network based radio map construction method for urban environment.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models A graph neural network based radio map construction method for urban environment

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06751f91-f90a-45b5-a492-92a0caf4f10b · outbound

This paper cites Stochastic gradient hamiltonian monte carlo.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Stochastic gradient hamiltonian monte carlo

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b69315d2-4983-4ddd-90ac-ca83434774f0 · outbound

This paper cites A method to reconstruct coverage loss maps based on matrix completion and adaptive sampling.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models A method to reconstruct coverage loss maps based on matrix completion and adaptive sampling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c61895c-0932-4a50-bd97-35d4ea452ffc · outbound

This paper cites Generating ckm using others’ data: Cross-ap ckm inference with deep learning.IEEE Transactions on Vehicular Technology, 75(2):3360–3365, 2026.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Generating ckm using others’ data: Cross-ap ckm inference with deep learning.IEEE Transactions on Vehicular Technology, 75(2):3360–3365, 2026

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cc8705f-edf8-41f8-bd14-4fa55a7b8845 · outbound

This paper cites Laplace redux-effortless bayesian deep learning.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Laplace redux-effortless bayesian deep learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 077caf52-aac7-4194-ac49-034941742498 · outbound

This paper cites Learning to communicate in uav-aided wireless networks: Map-based approaches.IEEE Internet of Things Journal, 6(2):1791–1802, 2019.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Learning to communicate in uav-aided wireless networks: Map-based approaches.IEEE Internet of Things Journal, 6(2):1791–1802, 2019

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1315bef1-7e28-4464-9ff2-fc39922f2df5 · outbound

This paper cites CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T05:34:20.032055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3c6b258-867a-4106-bce6-01e363992647 · outbound

This paper cites Dropout as a bayesian approximation: Repre- senting model uncertainty in deep learning.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Dropout as a bayesian approximation: Repre- senting model uncertainty in deep learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcf655f3-8d11-4ec6-8aa1-270101880905 · outbound

This paper cites Probabilistic backpropagation for scalable learning of bayesian neural networks.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Probabilistic backpropagation for scalable learning of bayesian neural networks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 818065cd-f11c-4d76-b895-6fefb50db57b · outbound

This paper cites Denoising diffusion probabilistic models.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Denoising diffusion probabilistic models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0ca902e-4127-4d5a-ae7c-2a628f8745f1 · outbound

This paper cites Channel knowledge map construction via guided flow matching.arXiv preprint arXiv:2601.06156, 2026.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Channel knowledge map construction via guided flow matching.arXiv preprint arXiv:2601.06156, 2026

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-30T05:34:20.035421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e57ba47d-837c-4308-8682-fc6d372966db · outbound

This paper cites Being bayesian, even just a bit, fixes overconfidence in relu networks.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Being bayesian, even just a bit, fixes overconfidence in relu networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6473c06a-64bb-4f5f-9058-8f6fe6a0c96e · outbound

This paper cites Simple and scal- able predictive uncertainty estimation using deep ensembles.Advances in neural information processing systems, 30, 2017.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Simple and scal- able predictive uncertainty estimation using deep ensembles.Advances in neural information processing systems, 30, 2017

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18188636-2aad-44d7-bc5a-2f0379707f06 · outbound

This paper cites an unresolved cited work.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dabc315-6e5d-4d98-9a44-a732bfdf9266 · outbound

This paper cites Pathloss prediction using deep learning with applications to cellular optimization and efficient d2d link scheduling.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Pathloss prediction using deep learning with applications to cellular optimization and efficient d2d link scheduling

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33b9d0d5-c3da-4fcb-a769-eca78dbbddaa · outbound

This paper cites Radiounet: Fast radio map estimation with convolutional neural networks.IEEE Transactions on Wireless Communications, 20(6):4001–4015, 2021.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Radiounet: Fast radio map estimation with convolutional neural networks.IEEE Transactions on Wireless Communications, 20(6):4001–4015, 2021

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 102afc16-20dd-4a68-863c-fed3ba3ef6d2 · outbound

This paper cites Automatic indoor radio map construction and localization via multipath fingerprint extrapolation.IEEE Trans- actions on Wireless Communications, 22(9):5814–5827, 2023.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Automatic indoor radio map construction and localization via multipath fingerprint extrapolation.IEEE Trans- actions on Wireless Communications, 22(9):5814–5827, 2023

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50447f2d-edf1-4869-b382-ea6fdbb21e14 · outbound

This paper cites an unresolved cited work.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ff6effa-36ff-46cc-be42-bf90a89c0d8e · outbound

This paper cites Rmtransformer: Accu- rate radio map construction and coverage prediction.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Rmtransformer: Accu- rate radio map construction and coverage prediction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64dbbd9d-6601-42b7-8de9-9098d3593252 · outbound

This paper cites Sparsely self-supervised generative adversarial nets for radio frequency estimation.IEEE Journal on Selected Areas in Communications, 37(11):2428–2442, 2019.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Sparsely self-supervised generative adversarial nets for radio frequency estimation.IEEE Journal on Selected Areas in Communications, 37(11):2428–2442, 2019

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7ae654f-5d5d-4707-8232-14562a79c748 · outbound

This paper cites An adaptive inverse-distance weighting spatial interpolation technique.Computers & Geosciences, 34:1044–1055, 2008.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models An adaptive inverse-distance weighting spatial interpolation technique.Computers & Geosciences, 34:1044–1055, 2008

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8de1fa8c-bfbe-4597-9bd8-0d1b7d432013 · outbound

This paper cites Polyzos, Alireza Sadeghi, Wei Ye, Steven Sleder, Kodjo Houssou, Jeff Calder, Zhi-Li Zhang, and Georgios B.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Polyzos, Alireza Sadeghi, Wei Ye, Steven Sleder, Kodjo Houssou, Jeff Calder, Zhi-Li Zhang, and Georgios B

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ceb47af-75a7-40c5-9c11-e6bdda66ea79 · outbound

This paper cites A scalable laplace approxi- mation for neural networks.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models A scalable laplace approxi- mation for neural networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 387931e1-bc03-4899-8e7a-5c2a3bc3e11d · outbound

This paper cites Blattmann, Dominik Lorenz, Patrick Esser, and Bj¨ orn Ommer.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Blattmann, Dominik Lorenz, Patrick Esser, and Bj¨ orn Ommer

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008fa288-7334-41ab-9e04-f3852815d45a · outbound

This paper cites Rem-u-net: Deep learning based agile rem prediction with energy-efficient cell-free use case.IEEE Open Journal of Signal Processing, 5:750–765, 2024.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Rem-u-net: Deep learning based agile rem prediction with energy-efficient cell-free use case.IEEE Open Journal of Signal Processing, 5:750–765, 2024

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a4d8ada-5eab-4d23-a50e-4464031ff7a2 · outbound

This paper cites Denoising Diffusion Implicit Models.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Denoising Diffusion Implicit Models

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-06-30T05:34:20.028857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b51dc891-7f8b-461d-8f9f-643e9a67d282 · outbound

This paper cites Deep completion autoencoders for radio map estimation.IEEE Transactions on Wireless Communications, 21(3):1710–1724, 2022.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Deep completion autoencoders for radio map estimation.IEEE Transactions on Wireless Communications, 21(3):1710–1724, 2022

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 808ef4a5-8625-42d6-86f2-53cf28bcfcad · outbound

This paper cites Learning radio maps for physical-layer security in the radio access.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Learning radio maps for physical-layer security in the radio access

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9c390ca-31dc-43db-b46c-d87bd9bb0e07 · outbound

This paper cites van Beers and J.P.C.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models van Beers and J.P.C

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2376a388-a5b0-451b-85ec-644ed80e420c · outbound

This paper cites Novel localization technique for next generation base stations using radio maps.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Novel localization technique for next generation base stations using radio maps

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb5ca31-dbff-482d-92b5-9368edacf3c3 · outbound

This paper cites an unresolved cited work.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f83e129d-0fc6-4cfe-b586-010cda5bec22 · outbound

This paper cites an unresolved cited work.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Unresolved cited work

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1d562cb-586d-43d6-973f-41a718191d1d · outbound

This paper cites How much data is needed for channel knowledge map con- struction?IEEE Transactions on Wireless Communications, 23(10):13011–13021, 2024.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models How much data is needed for channel knowledge map con- struction?IEEE Transactions on Wireless Communications, 23(10):13011–13021, 2024

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35393f57-7c69-4877-932e-077cd873f071 · outbound

This paper cites Dataset of pathloss and toa radio maps with localization application, 2022.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Dataset of pathloss and toa radio maps with localization application, 2022

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c37abf22-ea93-424d-8250-754cf9ffcd08 · outbound

This paper cites A tutorial on environment-aware commu- nications via channel knowledge map for 6g.IEEE Communications Surveys and Tutorials, 26:1478–1519, 2024.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models A tutorial on environment-aware commu- nications via channel knowledge map for 6g.IEEE Communications Surveys and Tutorials, 26:1478–1519, 2024

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bb50008-a385-46fe-8dd3-37c3254c5b4a · outbound

This paper cites Toward environment-aware 6g communications via channel knowledge map.IEEE Wireless Communications, 28:84–91, 6 2021.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Toward environment-aware 6g communications via channel knowledge map.IEEE Wireless Communications, 28:84–91, 6 2021

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbac9f4f-de75-4b3d-9c27-0b69f6509d55 · outbound

This paper cites Simultaneous navigation and radio mapping for cellular-connected uav with deep reinforcement learning.IEEE Trans- actions on Wireless Communications, 20(7):4205–4220, 2021.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Simultaneous navigation and radio mapping for cellular-connected uav with deep reinforcement learning.IEEE Trans- actions on Wireless Communications, 20(7):4205–4220, 2021

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db191a8c-57f8-4f6a-a4e0-7dacb5418a69 · outbound

This paper cites Radio map-based 3d path planning for cellular- connected uav.IEEE Transactions on Wireless Communications, 20(3):1975–1989, 2021.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Radio map-based 3d path planning for cellular- connected uav.IEEE Transactions on Wireless Communications, 20(3):1975–1989, 2021

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a634b714-cf44-43d8-98c6-aaa1b79bbd14 · outbound

This paper cites Rme-gan: A learning frame- work for radio map estimation based on conditional generative adversarial network.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Rme-gan: A learning frame- work for radio map estimation based on conditional generative adversarial network

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f9a8f72-1453-4426-9100-71e1f82975cf · outbound

This paper cites an unresolved cited work.

Active Learning for Channel Knowledge Map Construction via Bayesian Inference Diffusion Models Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-30T05:31:51.162101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.