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Paper Citation Record · LEDGER

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks

As of 19 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2501.06604.

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

pith.paper-citation-record.v1
2501.06604 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:02:23.131726Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

51 of 51 outbound references displayed

  • verified exact5
  • verified fuzzy31
  • unresolved15
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f3a9f3ce-92a6-4c4c-8797-dbb23ac7f611 · outbound

This paper cites A survey of wireless path loss prediction and coverage mapping methods,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks A survey of wireless path loss prediction and coverage mapping methods,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation bbcbae4b-6201-41dd-85fe-25ca8d9e40e3 · outbound

This paper cites Contextual Combinatorial Beam Management via Online Probing for Multiple Access mmWave Wireless Networks.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Contextual Combinatorial Beam Management via Online Probing for Multiple Access mmWave Wireless Networks

Reference 2

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local_arxiv, observed 2026-08-10T21:02:23.381126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ce7b8f15-1eb1-49ee-a40e-7fa442b24f45 · outbound

This paper cites Context-aware beam man- agement via online probing in combinatorial multi-armed bandits,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Context-aware beam man- agement via online probing in combinatorial multi-armed bandits,

Reference 3

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raw_fallback, observed 2026-08-10T21:02:23.861213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 576cd293-336a-436a-988a-07db2ac5841e · outbound

This paper cites Network digital twin: Context, enabling technologies, and opportuni- ties,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Network digital twin: Context, enabling technologies, and opportuni- ties,

Reference 4

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raw_fallback, observed 2026-08-10T21:02:23.848748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 75b03951-e566-4edb-ae36-92dc0206628a · outbound

This paper cites Optimizing synchronization delay for digital twin over wireless networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Optimizing synchronization delay for digital twin over wireless networks,

Reference 5

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raw_fallback, observed 2026-08-10T21:02:23.837191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation dc848993-8268-4b8a-86ec-0ceac0d622e7 · outbound

This paper cites A joint communication and computation framework for digital twin over wireless networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks A joint communication and computation framework for digital twin over wireless networks,

Reference 6

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raw_fallback, observed 2026-08-10T21:02:23.824081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation b2941492-4747-4ed3-b9e5-512849c7a424 · outbound

This paper cites Closed-form beamforming aided joint optimization for spectrum-and energy-efficient UA V-BS networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Closed-form beamforming aided joint optimization for spectrum-and energy-efficient UA V-BS networks,

Reference 7

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raw_fallback, observed 2026-08-10T21:02:23.810192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9b4ab9c1-59e2-43b4-9cbf-3059d4c181a3 · outbound

This paper cites Analysis of drone as- sisted network coded cooperation for next generation wireless network,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Analysis of drone as- sisted network coded cooperation for next generation wireless network,

Reference 8

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raw_fallback, observed 2026-08-10T21:02:23.797193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation bd2c0d90-1cf1-4ab3-9a0d-57cdc240242a · outbound

This paper cites Ray tracing for radio propagation modeling: Principles and applications,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Ray tracing for radio propagation modeling: Principles and applications,

Reference 9

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no resolver link, observed 2026-08-10T21:02:22.953945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:22.953945Z digest=sha256:fff68ffa8bdfb095eed513ed2a30490f1aec31a1be4c9ce0cd3a66722a221bec

Observation 6fa98658-e58d-441d-bd09-2211b64b7089 · outbound

This paper cites Map-driven mmwave link quality prediction with spatial-temporal mobility awareness,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Map-driven mmwave link quality prediction with spatial-temporal mobility awareness,

Reference 10

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raw_fallback, observed 2026-08-10T21:02:23.777641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1cd871a4-d328-451e-8d10-596d8d511f20 · outbound

This paper cites Environment-aware link quality prediction for millimeter-wave wireless lans,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Environment-aware link quality prediction for millimeter-wave wireless lans,

Reference 11

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raw_fallback, observed 2026-08-10T21:02:23.765694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 96e44a74-0148-4a3f-b2b8-97175d6598f2 · outbound

This paper cites Kriging-based interference power constraint: Integrated design of the radio environment map and transmission power,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Kriging-based interference power constraint: Integrated design of the radio environment map and transmission power,

Reference 12

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no resolver link, observed 2026-08-10T21:02:22.965770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:22.965770Z digest=sha256:5e4e3413c6e35c6be0ab4c6566a2ca72086d8a4b1e9c69a87a7eaeefed2a7ec4

Observation bf64dfef-b674-4bb4-8833-f0563a0378d0 · outbound

This paper cites Aerial spectrum surveying: Radio map estimation with autonomous UA Vs,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Aerial spectrum surveying: Radio map estimation with autonomous UA Vs,

Reference 13

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raw_fallback, observed 2026-08-10T21:02:23.744208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 85ef38e9-55b5-41d8-9108-241958894c1a · outbound

This paper cites Propagation map reconstruction via interpolation assisted matrix completion,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Propagation map reconstruction via interpolation assisted matrix completion,

Reference 14

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raw_fallback, observed 2026-08-10T21:02:23.732036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:22.973349Z digest=sha256:9a779fd4ec70f10ed3f9a1c3374ae2345c53e1f880fe03fafbd73d8b12ddd07f

Observation 4860fad6-c5db-453e-8b14-9fe708d6a9cb · outbound

This paper cites Reducing the effects of motion artifacts in fmri: A structured matrix completion approach,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Reducing the effects of motion artifacts in fmri: A structured matrix completion approach,

Reference 15

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raw_fallback, observed 2026-08-10T21:02:23.719627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9a508841-1be5-489b-8d1f-5d7f970b8e18 · outbound

This paper cites Cognitive radio spectrum prediction using dictionary learning,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Cognitive radio spectrum prediction using dictionary learning,

Reference 16

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raw_fallback, observed 2026-08-10T21:02:23.708162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 272a46fd-7392-4974-b0b7-1a406fc31405 · outbound

This paper cites Spatial signal strength predic- tion using 3d maps and deep learning,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Spatial signal strength predic- tion using 3d maps and deep learning,

Reference 17

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raw_fallback, observed 2026-08-10T21:02:23.696587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7e1bd06d-ab32-4ba3-9fd5-779a97444243 · outbound

This paper cites Deep completion autoencoders for ra- dio map estimation,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Deep completion autoencoders for ra- dio map estimation,

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:22.989159Z digest=sha256:f66e660603d3b9e6c14b1405c74ae1f51f5b270bed13cfe9359d08b81868bc0d

Observation 9b97355a-e8b4-49ff-8176-698ba91077b6 · outbound

This paper cites Machine learning-based urban canyon path loss prediction using 28 ghz manhattan measurements,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Machine learning-based urban canyon path loss prediction using 28 ghz manhattan measurements,

Reference 19

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raw_fallback, observed 2026-08-10T21:02:23.675291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:22.992917Z digest=sha256:d5797225f09fcf0dcdd2e1dc91291b6679f6a435aa5a1cdc743663705634934b

Observation 30110a0e-a21d-4ada-9859-3b0e89ff652f · outbound

This paper cites Transformer- based neural surrogate for link-level path loss prediction from variable- sized maps,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Transformer- based neural surrogate for link-level path loss prediction from variable- sized maps,

Reference 20

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raw_fallback, observed 2026-08-10T21:02:23.662561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 2431aeac-8966-463e-97fe-3f50b1f712d0 · outbound

This paper cites Radiounet: Fast radio map estimation with convolutional neural networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Radiounet: Fast radio map estimation with convolutional neural networks,

Reference 21

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Unavailable: canonical work link unavailable.

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Observation c11944b4-b214-48b1-a17f-d7d030b46a22 · outbound

This paper cites A scalable and generalizable pathloss map prediction,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks A scalable and generalizable pathloss map prediction,

Reference 22

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no resolver link, observed 2026-08-10T21:02:23.005770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.005770Z digest=sha256:939a0f86f588a81fc8f83ee7a0894f3fc4eea6f211e276def1e006808c0ed812

Observation 86e149cf-6031-44c6-92c6-f40b0fa1b1d7 · outbound

This paper cites Da-cgan: A framework for indoor radio design using a dimension-aware conditional generative adversarial network,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Da-cgan: A framework for indoor radio design using a dimension-aware conditional generative adversarial network,

Reference 23

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raw_fallback, observed 2026-08-10T21:02:23.633773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3b15882e-48d3-4dd7-b054-e885044cf4e1 · outbound

This paper cites Radio map estimation using a generative adversarial network and related business aspects,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Radio map estimation using a generative adversarial network and related business aspects,

Reference 24

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raw_fallback, observed 2026-08-10T21:02:23.621050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 09dfff27-d230-45a7-b69a-90d52dc6bcd8 · outbound

This paper cites Access-point centered window- based radio-map generation network,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Access-point centered window- based radio-map generation network,

Reference 25

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raw_fallback, observed 2026-08-10T21:02:23.608100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 804c4aa5-8008-4157-aa12-c9bfada86a0b · outbound

This paper cites RME-GAN: a learning frame- work for radio map estimation based on conditional generative adver- sarial network,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks RME-GAN: a learning frame- work for radio map estimation based on conditional generative adver- sarial network,

Reference 26

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raw_fallback, observed 2026-08-10T21:02:23.595833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation eab8fcb8-9051-4d68-bdd3-c3eafd3a4e07 · outbound

This paper cites IRGAN: CGAN-based indoor radio map prediction,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks IRGAN: CGAN-based indoor radio map prediction,

Reference 27

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raw_fallback, observed 2026-08-10T21:02:23.583855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.029175Z digest=sha256:7233095fad4088b1087b670edd76ee4ac761e495ca2e67cf0322ddc8e39e1739

Observation a99be7c4-4255-4c7b-929f-0e3cf7f1c222 · outbound

This paper cites Denoising diffusion probabilistic models,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Denoising diffusion probabilistic models,

Reference 28

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no resolver link, observed 2026-08-10T21:02:23.033452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.033452Z digest=sha256:f8e4eb636a82dfc2a9d586afd50e439971f986725099b873c96c3109585650ab

Observation 6a22fd5f-5b9a-4f1e-a299-a0af7919aca3 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks High- resolution image synthesis with latent diffusion models,

Reference 29

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no resolver link, observed 2026-08-10T21:02:23.037692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.037692Z digest=sha256:40dc796e063643d6ee05d430ef6ff7a53ada02edeea3f596a2bb5f4af03626ce

Observation 4cc6877c-d2a9-40a6-9b37-647707472ae7 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Imagen Video: High Definition Video Generation with Diffusion Models

Reference 30

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no resolver link, observed 2026-08-10T21:02:23.041931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.041931Z digest=sha256:0a0c88b9f131895e223545169e7e18b68491af89a8edfe44781d683638bf4a4d

Observation 0856b783-fbb9-458a-a687-5446a2c9269b · outbound

This paper cites DiffWave: A Versatile Diffusion Model for Audio Synthesis.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks DiffWave: A Versatile Diffusion Model for Audio Synthesis

Reference 31

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no resolver link, observed 2026-08-10T21:02:23.046818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.046818Z digest=sha256:00b4a23ffb6c9eca618eec93353e3f9e6aa82ed8ebaa8ac07693a5c2c1e2bb38

Observation 38f72d31-dbd0-4f0a-a84e-b4cc53e5bdbf · outbound

This paper cites Csdi: Conditional score- based diffusion models for probabilistic time series imputation,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Csdi: Conditional score- based diffusion models for probabilistic time series imputation,

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.051229Z digest=sha256:ca0e052152d3ff0d8857fb45ac904b16d42fbc901becb3405171ffffc4446f01

Observation 3884079d-25ff-4c23-a5c8-51c4524ff936 · outbound

This paper cites Generative time series forecasting with diffusion, denoise, and disentanglement,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Generative time series forecasting with diffusion, denoise, and disentanglement,

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.548378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.055812Z digest=sha256:7101b97a315ad595e9d7380bb5d0689e7b1865f475223457e23024488815ab71

Observation 0c374138-86b4-4e36-b6e3-0d96ff5a891b · outbound

This paper cites A survey on diffusion models for time series and spatio-temporal data,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks A survey on diffusion models for time series and spatio-temporal data,

Reference 34

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no resolver link, observed 2026-08-10T21:02:23.059617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.059617Z digest=sha256:b7dd46b3a90fb790167d12695dbb808e247e2880ac8227661921232f1ec39a9a

Observation 485b457f-af42-44ca-927d-01ae36d4dcd1 · outbound

This paper cites Dyffusion: A dynamics-informed diffusion model for spatiotemporal forecasting,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Dyffusion: A dynamics-informed diffusion model for spatiotemporal forecasting,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.535883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.063780Z digest=sha256:cf3908eb67ea0e01a77240580c13050b7b1c321934fd360f09837d8bd116c0db

Observation a3f82983-1e2a-48d7-b324-8f93d05b43b0 · outbound

This paper cites Score-based generative models for robust channel estimation,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Score-based generative models for robust channel estimation,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.521752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.069190Z digest=sha256:b7eff36958d3abd705feb686529d8a058deee6a6b1db3ef76858c8bc47ecec89

Observation 05aa6994-ee3c-42a7-88e6-cef17c5d2801 · outbound

This paper cites CDDM: Channel denoising diffusion models for wireless communications,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks CDDM: Channel denoising diffusion models for wireless communications,

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.505836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.072973Z digest=sha256:e0611ebc5cd6b3dd07d54e33485e6bcc30443b165d3d434fb89d9c0f7956ad04

Observation 3fb63608-962e-4824-a8f1-578b5c732276 · outbound

This paper cites Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications

Reference 38

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verified exact
local_arxiv, observed 2026-08-10T21:02:23.257048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.077479Z digest=sha256:43c72614ef099b571cda2d06befbe86a1bb6a1eb8894caa87027105ac27fc002

Observation 9abcf276-ac02-4ffd-8fd0-a4902c75fb0b · outbound

This paper cites Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models

Reference 39

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verified exact
local_arxiv, observed 2026-08-10T21:02:23.230849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.081656Z digest=sha256:f5f470d38bd1ab6913de848dfc8f8a7e71b05cf8d8cc254b94329e66027d1142

Observation 13720560-7338-418c-a7a9-590487c905da · outbound

This paper cites Learning end-to-end channel coding with diffusion models,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Learning end-to-end channel coding with diffusion models,

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.491066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.085756Z digest=sha256:0ccc8ec92fdb0184a608c1e322330a9b1a7cc5e1d984ecaf9af18ae1032646e7

Observation b1a18da5-4e82-4f56-be60-847dabc106a8 · outbound

This paper cites Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study

Reference 41

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verified exact
local_arxiv, observed 2026-08-10T21:02:23.207138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.090145Z digest=sha256:47352d214453d8ebf238733b218633bfbae32a0f5538a34086ad7bea176ac11c

Observation e9d7b988-0bec-4c62-ab58-ed6845e02390 · outbound

This paper cites A hybrid wireless image transmission scheme with diffusion,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks A hybrid wireless image transmission scheme with diffusion,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.476475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.094967Z digest=sha256:983625106c46d06ac60939d7930fe58ee51e4ccb833b3490376b4a58c2c33429

Observation 564a4e00-e14d-4714-b639-a06d5e70beb7 · outbound

This paper cites High Perceptual Quality Wireless Image Delivery with Denoising Diffusion Models.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks High Perceptual Quality Wireless Image Delivery with Denoising Diffusion Models

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-10T21:02:23.186844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.099895Z digest=sha256:103190fc72b8fdfac9acbcdf306faa16621838a28150f52291abeed488950519

Observation c95b80c8-74d8-438a-a9bd-4e8173d693f4 · outbound

This paper cites Commin: Semantic image communications as an inverse problem with inn-guided diffusion models,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Commin: Semantic image communications as an inverse problem with inn-guided diffusion models,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.463375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.104392Z digest=sha256:f5e80a02631c72e83042dd0f0f6913e1053fabed35455b8c8ea92f8bd6dced8e

Observation 21cc2447-51ff-4704-9857-2b351976ffea · outbound

This paper cites Rm-gen: Conditional diffusion model-based radio map generation for wireless networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Rm-gen: Conditional diffusion model-based radio map generation for wireless networks,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.450828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.107788Z digest=sha256:9b032a8a2eac6472bea183c2a5477557e1bff9393cfe75d2bb8de706adb2a11e

Observation 4cbd57ca-d41c-4def-a0c0-c65ee0d4066f · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks U-net: Convolutional networks for biomedical image segmentation,

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T21:02:23.111595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.111595Z digest=sha256:d264f194e355784d8eb3f311565fe7eab95d5f327941885ec998ad105badf41d

Observation bcfab49a-f3d6-4949-a189-0c4b22d2c267 · outbound

This paper cites 6G wireless channel measurements and models: Trends and challenges,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks 6G wireless channel measurements and models: Trends and challenges,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.427532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.115551Z digest=sha256:3b87927b2367cdbf37cc74f755696acb22ae81a295f57f1928c15d5481c27470

Observation 0969f151-bc3b-401a-994c-0547c6bdc783 · outbound

This paper cites Comparison of ray tracing simulations and millimeter wave channel sounding mea- surements,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Comparison of ray tracing simulations and millimeter wave channel sounding mea- surements,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:02:23.409757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T21:02:23.119152Z digest=sha256:126c0bed9daf5b4b54a749c974b411e703156744b111cd132fafbc675c19eb47

Observation 88cf069b-3cab-4c12-a486-50aabfe11c2f · outbound

This paper cites Conditional Generative Adversarial Nets.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Conditional Generative Adversarial Nets

Reference 49

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unresolved
no resolver link, observed 2026-08-10T21:02:23.122578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.122578Z digest=sha256:2ec32c79691870ddba4d1fda86a28565a8b9b962d26581ee0555d830c2aca593

Observation fbca32a9-fe09-42a4-b478-0f1b7c432e1c · outbound

This paper cites Image-to-image translation with conditional adversarial networks,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Image-to-image translation with conditional adversarial networks,

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T21:02:23.127207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.127207Z digest=sha256:298a099b23cbdfe396034226503e9bd472eae4c4b3fe1dd411cc055842f9aaaa

Observation 61fdc030-f2c2-4f62-8cf2-b2b5301536ac · outbound

This paper cites Generative adversarial networks: An overview,.

Denoising Diffusion Probabilistic Model for Radio Map Estimation in Generative Wireless Networks Generative adversarial networks: An overview,

Reference 51

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unresolved
no resolver link, observed 2026-08-10T21:02:23.131726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:23.131726Z digest=sha256:99454b3b5de05319eec0b08f463e09d40099c4c7cd4b2a604b699e91685b9cb3

Pith citing papers

No inbound Pith citation observations are available.