Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:30:59.377062Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:2608.11917.
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 2026-08-16T00:30:59.377062Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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
100 of 300 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression A Bayesian Sampling Approach to Exploration in Reinforcement Learning
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Reinforcement
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Simpson, Daniel and Rue, H
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Reference 21
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Kalman filters as the steady-state solution of gradient descent on variational free energy
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Unresolved cited work
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression and Choo, Xuan and Bekolay, Trevor and DeWolf, Travis and Tang, Yichuan and Rasmussen, Daniel , year = 2012, month = nov, journal =
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression RvS: What is Essential for Offline RL via Supervised Learning?
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A Factor Graph Approach to Scalable Multi-Output Gaussian Process Regression Resolving uncertainty on the fly: Modeling adaptive driving behavior as active inference
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