Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:31:49.583230Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 0 inbound Pith citation observations for arXiv:2608.04430.
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 2026-08-08T18:31:49.583230Z
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
74 of 74 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 37407379-fbef-436b-bec2-868b78e1182c · outbound
An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Unresolved cited work
Reference 1
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Unresolved cited work
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Van Der Pol, J
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Arasaratnam, S
Reference 10
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Doucet, N
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Ristic, S
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Khodarahmi, V
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Snyder, T
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Terejanu, P
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Zhang, Y
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Unresolved cited work
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Tuggle, R
Reference 24
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Raitoharju, Á
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Alspach, H
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Faubel, J
Reference 29
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Faubel, D
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Leutnant, A
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Singla, T
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Cun, An efficient adaptive weights update scheme for a gaussian mixture filter, in: 2021 33rd Chinese Control and Decision Conference (CCDC), 2021, pp
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Vittaldev, R
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Reference 52
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Reference 58
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
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Reference 64
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Reference 65
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Reference 66
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Score-Based Generative Modeling through Stochastic Differential Equations
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation Albergo, N
Reference 72
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation ,2δ](Appendix B.2) = ∞X n=1 2 n−1 n! Dnv(x)[δ,
Reference 73
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An adaptive split-combine Gaussian mixture filter for nonlinear and multimodal state estimation ,δ].(Appendix B.4) Hence, the numerator in (13) is given by: 1 2 (v(x+ 2δ)−v(x)) −[v(x+δ)−v(x)] (Appendix B.5) = ∞X n=1 2n−1 −1 n! Dnv(x)[δ,
Reference 74
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No inbound Pith citation observations are available.