Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:19:58.188166Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2507.08734.
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 2026-08-06T18:19:58.188166Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
25 of 25 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 2e59bb90-9d01-44d7-bdc8-ca1e49d305fd · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Boelts, M
Reference 1
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Observation a398ef1a-9aa3-4243-8868-df6972fd9f69 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation The frontier of simulation-based inference
Reference 2
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Observation 55673558-26e1-40d9-b8a0-1a7cc5a05fa6 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Density estimation using Real NVP
Reference 3
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Observation 26434434-2423-4e04-91a0-3dd0f09c7f09 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work
Reference 4
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Observation 849105cc-b0a2-4275-bb15-2833cf59290d · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Grelaud, J.-M
Reference 5
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Observation 2b4a31b6-e282-4672-a714-7c10fcf7c9d2 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Likelihood-free mcmc with amortized approximate likelihood ratios
Reference 6
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Observation ab4b77e4-6cf7-459d-9442-dc184e96a58a · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work
Reference 7
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Observation 8ed90ebe-f428-4eae-81b6-713c96d526ae · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Marin, P
Reference 8
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Observation 603cb695-590a-43cb-8a91-bc700cc4b610 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator
Reference 9
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Observation 82948148-d487-4949-843e-b568effbb586 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Sequential monte carlo samplers
Reference 10
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Observation 52872c63-0333-4d9d-87c8-84b3a99cc7ec · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Newton and Adrian E
Reference 11
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Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work
Reference 12
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Observation 2ff997e2-de5f-405b-9854-36d9063a91bc · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Fast -free inference of simulation models with bayesian conditional density estimation
Reference 13
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Observation b2c6b92c-c770-4f2a-8440-7372fd61e05b · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Masked Autoregressive Flow for Density Estimation
Reference 14
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Observation cacc4f39-1eb5-49e6-81f9-5a8e191fd13d · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows
Reference 15
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Observation 5d3e6584-b649-4dc4-8317-c4f92aae8786 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Normalizing flows for probabilistic modeling and inference
Reference 16
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Observation 7d79609d-e1a9-45be-b607-9a2ae8d6aef8 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Price, Davide Piras, Alessio Spurio Mancini, and Jason D
Reference 17
Source-reported events for the cited work
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Observation 3d4e2189-7574-4a88-a0df-f98aac2ec427 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Pritchard, M.T
Reference 18
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Observation 9ae735bd-2cf4-44b6-95f2-a83c9d446c7a · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work
Reference 19
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Observation 80fb2e9a-5d73-4c73-9205-bcb645aa9f35 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Robert and George Casella
Reference 20
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Observation d069eeaf-62df-4730-a183-eec1e7931a10 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Zuko : Normalizing flows in pytorch, 2022
Reference 21
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Observation 58cbb37a-d7ed-4434-b3a0-300479327864 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work
Reference 22
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Observation 57eea1b5-b6e1-4c59-aa85-2854188eba0a · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Spurio Mancini, M.M
Reference 23
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Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Balding, Robert C
Reference 24
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Observation f47b665d-a669-4879-9090-51c23bc93141 · outbound
Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Lewis, Yu Fan, Lynn Kuo, and Ming-Hui Chen
Reference 25
Source-reported events for the cited work
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No inbound Pith citation observations are available.