Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Machine Learning for Inverse Problems and Data Assimilation
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.10523.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:17:30.866687Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 2c300564-c252-44e3-84a7-541d87329e9f · inbound
Long-time accuracy of ensemble Kalman filters for chaotic and machine-learned dynamical systems cites this paper.
Long-time accuracy of ensemble Kalman filters for chaotic and machine-learned dynamical systems Machine Learning for Inverse Problems and Data Assimilation
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:28:04.606079Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05bbd0c3-86c6-4aa7-9176-ac3c3b59a025 · inbound
Flow Matching for Efficient and Scalable Data Assimilation cites this paper.
Flow Matching for Efficient and Scalable Data Assimilation Machine Learning for Inverse Problems and Data Assimilation
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:17:30.866687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 332d795e-9608-4188-8917-09066487ddc6 · inbound
FLUID: Flow-based Unified Inference for Dynamics cites this paper.
FLUID: Flow-based Unified Inference for Dynamics Machine Learning for Inverse Problems and Data Assimilation
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-08-11T02:18:10.673103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8d3a949c-47eb-49dc-a0b4-deaa826463e2 · inbound
Statistical finite elements for sequential data synthesis in solid dynamics cites this paper.
Statistical finite elements for sequential data synthesis in solid dynamics Machine Learning for Inverse Problems and Data Assimilation
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-08-11T02:18:10.673103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fbcc6604-0fa4-440c-a936-da9862398e81 · inbound
Amortized Energy-Based Bayesian Inference cites this paper.
Amortized Energy-Based Bayesian Inference Machine Learning for Inverse Problems and Data Assimilation
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-08-11T02:18:10.673103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7907724b-d5ae-49a1-905c-ae7e2a169938 · inbound
Continuous Data Assimilation with Learned Surrogate Dynamics cites this paper.
Continuous Data Assimilation with Learned Surrogate Dynamics Machine Learning for Inverse Problems and Data Assimilation
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-08-11T02:18:10.673103Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.