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Paper Citation Record · LEDGER

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks

As of 22 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2606.22301.

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

pith.paper-citation-record.v1
2606.22301 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T10:13:55.432853Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T16:59:03.310622Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b93bb7b-b7c0-4f96-b721-70a2882defaa · outbound

This paper cites an unresolved cited work.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Unresolved cited work

Reference 1

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no resolver link, observed 2026-06-26T10:13:55.432853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:a414bf1d46ae06be4ae5bdbd4d8c2d44030c1c601cb708c032b37f59148888f8

Observation e38e9c69-a7eb-4ab0-9429-e0d1f1cc175b · outbound

This paper cites El Gamal and Y .-H.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks El Gamal and Y .-H

Reference 2

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:8cee381a31ac479a7ba40f3dd7b6dc44df0043124750e6d61e1ee74f36659211

Observation b58e8fae-e2cc-4e1d-a287-f056eec8e2f4 · outbound

This paper cites Capacity of multi-antenna Gaussian channels,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Capacity of multi-antenna Gaussian channels,

Reference 3

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no resolver link, observed 2026-06-26T10:13:55.432853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:53caf3ba27f0e779df58411617b8cf7e14dd41d485ba42e276f937dec36702e9

Observation 6d0d81e4-b382-47ba-974c-3198c1f0de68 · outbound

This paper cites Gradient of mutual information in linear vector Gaussian channels,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Gradient of mutual information in linear vector Gaussian channels,

Reference 4

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no resolver link, observed 2026-06-26T10:13:55.432853Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:30da429794a6566e5356f359001ae833555bb40f8c07569fbb745ca9b6dbc9b2

Observation e69346b3-f8bd-4e18-9a9f-575e50ed245e · outbound

This paper cites Multiaccess fading channels—Part I: Polymatroid structure, optimal resource allocation, and throughput capacities,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Multiaccess fading channels—Part I: Polymatroid structure, optimal resource allocation, and throughput capacities,

Reference 5

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no resolver link, observed 2026-06-26T10:13:55.432853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:a5b634161e0ae0615c55eca8a39fcac13f919edcc3546703010177c9ed430968

Observation 12261d30-aa82-4a57-b457-b5bb6f8fafe0 · outbound

This paper cites PyTorch: An imperative style, high-performance deep learning library,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks PyTorch: An imperative style, high-performance deep learning library,

Reference 6

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no resolver link, observed 2026-06-26T10:13:55.432853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:bd22d0242ccecfcf81acbfe62a840edff6d26f8422415053a61529d05bed0b2b

Observation 809225df-8c8c-4feb-88bc-448ed082c176 · outbound

This paper cites A new achievable rate region for the interference channel,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks A new achievable rate region for the interference channel,

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:da665c93d95903bc633d98efec4efb32b1220aac174623e0d230184341866895

Observation 7b554f98-a204-44f5-891f-ff1cbd0bfdfd · outbound

This paper cites Capacity theorems for the relay channel,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Capacity theorems for the relay channel,

Reference 8

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no resolver link, observed 2026-06-26T10:13:55.432853Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:81b4385617d2e05fde64091abc51786e3c09d40c9e8793cad8c9043614ee9110

Observation 184f4d83-1403-45b5-a3fa-4b5ea32dbe5b · outbound

This paper cites On the achievable throughput of a multiantenna Gaussian broadcast channel,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks On the achievable throughput of a multiantenna Gaussian broadcast channel,

Reference 9

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no resolver link, observed 2026-06-26T10:13:55.432853Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:961cf403701f0b62f338a09a4d181fff6888290035f54c1294983ce420e30cc0

Observation 7d43e344-e34c-4a12-adbf-f07629d941b2 · outbound

This paper cites Mutual Information Optimization via K-Recursion and Automatic Differentiation for Linear Gaussian Wireless Networks.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Mutual Information Optimization via K-Recursion and Automatic Differentiation for Linear Gaussian Wireless Networks

Reference 10

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verified exact
local_arxiv, observed 2026-07-04T09:19:43.525428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:c1a76c6aaabb98f370f9a4b21abeec26e715f02b095620d61407e8e4f7442dd7

Observation 3be956a4-24b2-4d83-9067-873c2a77b764 · outbound

This paper cites Information gradient for directed acyclic graphs: A score-based framework for end-to-end mutual information maximization,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Information gradient for directed acyclic graphs: A score-based framework for end-to-end mutual information maximization,

Reference 11

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verified exact
arxiv_id, observed 2026-07-04T09:19:43.529031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:b3bd1d2f545f9aa3af4db564d708a2115e3633c6107c322123f32f4776b773da

Observation 06291b3c-0dd5-4724-b070-1ebe08362e66 · outbound

This paper cites Mutual information neural estimation,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Mutual information neural estimation,

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:c69ca2816b2e4332a7a6621e75936eba6552795b05b49e32f5660e7e251dd57f

Observation 8de31099-9d1f-44f0-af68-0b9ba0a667c2 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Representation Learning with Contrastive Predictive Coding

Reference 13

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verified exact
local_arxiv, observed 2026-07-04T09:19:43.531895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:49264a575e0d8eaf21521be592cb8fbc73cf62e80826cec01b9b2f6c5e534e99

Observation 41b131eb-1aab-4125-abb8-15f7b88edaaf · outbound

This paper cites Automatic differentiation in machine learning: A survey,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Automatic differentiation in machine learning: A survey,

Reference 14

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source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:5b9f04788696e82460c4fc5351ea7c1fb4b036806af9cd35d39ac49948ad47a5

Observation 8fe436c0-1315-4c89-99d0-39f4c4cbd1d1 · outbound

This paper cites an unresolved cited work.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Unresolved cited work

Reference 15

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source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:c9b08532b3233d9c66be040545a620628f86fe2db420d1d495436e69db369d29

Observation 38c28c14-65f8-49c0-a5ab-27f57bfe6a95 · outbound

This paper cites Gaussian influence diagrams,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Gaussian influence diagrams,

Reference 16

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source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:4f1f5a1f3c1efafd9f01f186ed0f47da6a1844757b3b210a679048542bbff1a8

Observation ef755ea5-0e73-4b1f-bb61-792c45ea5347 · outbound

This paper cites Learning Gaussian networks,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Learning Gaussian networks,

Reference 17

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source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:e020ecee3d364d18aa3967c0385f3ee752b42a6138fdae1f63106bfa7bd74a83

Observation e4be3e67-0c72-4866-9db5-650380eeea3b · outbound

This paper cites Trek separation for Gaussian graphical models,.

Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks Trek separation for Gaussian graphical models,

Reference 18

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-26T10:13:55.432853Z digest=sha256:0e040e0728da0b43377f07812940271191c0b5913bf8acbc9955013f3c98a4d3

Pith citing papers

Observation a5a378d4-40ac-4eb3-bb34-482b1c94c1ff · inbound

A Differentiable Covariance Calculus for Linear Gaussian Bayesian Networks cites this paper.

A Differentiable Covariance Calculus for Linear Gaussian Bayesian Networks Differentiable Conditional Mutual Information for Multi-Terminal Linear Gaussian Wireless Networks

Reference 2

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