Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:51:15.764750Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 0 inbound Pith citation observations for arXiv:2501.13109.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:51:15.764750Z
One-hop event checks from named stored sources.
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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
78 of 78 outbound references displayed
External citation measurements
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging 27(1) 95–111
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging sLORETA is equivalent to single dipole scanning
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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Bayesian Model Parameter Learning in Linear Inverse Problems: Application in EEG Focal Source Imaging Unresolved cited work
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