Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-17T02:49:07.511402Z
Paper Citation Record · LEDGER
Differentially Private and Federated Structure Learning in Bayesian Networks
As of 12 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2512.01708.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
10 of 10 outbound references displayed
- verified exact1
- verified fuzzy4
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b7fc3d33-2b9b-4054-95f8-b3f2f2e0c67e · outbound
This paper cites The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise.
Differentially Private and Federated Structure Learning in Bayesian Networks The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T02:51:28.136134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b7166821-f15a-4454-b6b7-c16066bdf0b0 · outbound
This paper cites Masked Gradient-Based Causal Structure Learning.
Differentially Private and Federated Structure Learning in Bayesian Networks Masked Gradient-Based Causal Structure Learning
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T02:51:28.139541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f627dea6-70ca-4a40-ba2b-98614c5aa65b · outbound
This paper cites an unresolved cited work.
Differentially Private and Federated Structure Learning in Bayesian Networks Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T02:51:28.897622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 30c3b11e-318c-4fab-8aff-07143c1f4b54 · outbound
This paper cites an unresolved cited work.
Differentially Private and Federated Structure Learning in Bayesian Networks Unresolved cited work
Reference 4
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T02:51:28.887941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ab96c0b0-2441-481c-8c52-531ff152dcf7 · outbound
This paper cites This additive noise term is sampled, for each variable, from a standard normal distributionN(0,1).
Differentially Private and Federated Structure Learning in Bayesian Networks This additive noise term is sampled, for each variable, from a standard normal distributionN(0,1)
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T02:51:28.885682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 06448338-eddd-4399-9b1e-4db1a5699c68 · outbound
This paper cites an unresolved cited work.
Differentially Private and Federated Structure Learning in Bayesian Networks Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T02:51:28.899633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e69f05b6-fd75-46bc-8da2-61e1c0fa73f9 · outbound
This paper cites For DP-Fed-BNSL,bis the sensitivity bound used for the 23 Gaussian mechanism applied to privatize the covariance matrices, as described by Wang (2018).
Differentially Private and Federated Structure Learning in Bayesian Networks For DP-Fed-BNSL,bis the sensitivity bound used for the 23 Gaussian mechanism applied to privatize the covariance matrices, as described by Wang (2018)
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T02:51:28.895431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ec794253-c874-448d-bebe-a25b2e8ea1df · outbound
This paper cites an unresolved cited work.
Differentially Private and Federated Structure Learning in Bayesian Networks Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T02:51:28.901717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation a11a1367-f6d7-4d44-a657-c68f1c4eef20 · outbound
This paper cites G Implementation and Computing Resources All experiments were conducted on CPUs, either on a personal computer or using a commodity cluster.
Differentially Private and Federated Structure Learning in Bayesian Networks G Implementation and Computing Resources All experiments were conducted on CPUs, either on a personal computer or using a commodity cluster
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T02:51:28.892997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation c7090dbe-ae37-41b6-b299-c918ac0f9940 · outbound
This paper cites Regarding licenses, the reused code for NOTEARS-ADMM (Ng and Zhang.
Differentially Private and Federated Structure Learning in Bayesian Networks Regarding licenses, the reused code for NOTEARS-ADMM (Ng and Zhang
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T02:51:28.890577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
No inbound Pith citation observations are available.