Paper Citation Record · LEDGER

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation

As of 23 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.

pith.paper-citation-record.v1
2507.08734 v1

Coverage vector

measured 25 of 25 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

25 of 25 outbound references displayed

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External citation measurements

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Outbound references

Observation 2e59bb90-9d01-44d7-bdc8-ca1e49d305fd · outbound

This paper cites Boelts, M.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Boelts, M

Reference 1

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This paper cites The frontier of simulation-based inference.

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

This paper cites Density estimation using Real NVP.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Density estimation using Real NVP

Reference 3

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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

This paper cites Grelaud, J.-M.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Grelaud, J.-M

Reference 5

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This paper cites Likelihood-free mcmc with amortized approximate likelihood ratios.

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

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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

This paper cites Marin, P.

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

This paper cites Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator.

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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This paper cites Sequential monte carlo samplers.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Sequential monte carlo samplers

Reference 10

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This paper cites Newton and Adrian E.

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

This paper cites Fast -free inference of simulation models with bayesian conditional density estimation.

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

This paper cites Masked Autoregressive Flow for Density Estimation.

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

This paper cites Sequential neural likelihood: Fast likelihood-free inference with autoregressive flows.

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

This paper cites Normalizing flows for probabilistic modeling and inference.

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

This paper cites Price, Davide Piras, Alessio Spurio Mancini, and Jason D.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Price, Davide Piras, Alessio Spurio Mancini, and Jason D

Reference 17

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Observation 3d4e2189-7574-4a88-a0df-f98aac2ec427 · outbound

This paper cites Pritchard, M.T.

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

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Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Unresolved cited work

Reference 19

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This paper cites Robert and George Casella.

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

This paper cites Zuko : Normalizing flows in pytorch, 2022.

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

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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

This paper cites Spurio Mancini, M.M.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Spurio Mancini, M.M

Reference 23

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This paper cites Balding, Robert C.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Balding, Robert C

Reference 24

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This paper cites Lewis, Yu Fan, Lynn Kuo, and Ming-Hui Chen.

Estimating Marginal Likelihoods in Likelihood-Free Inference via Neural Density Estimation Lewis, Yu Fan, Lynn Kuo, and Ming-Hui Chen

Reference 25

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Pith citing papers

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