Paper Citation Record · LEDGER

Communicating Likelihoods with Normalising Flows

As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2502.09494.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.09494 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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A source-named dated measurement, never combined with another source.

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Reference resolution

62 of 62 outbound references displayed

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External citation measurements

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Outbound references

Observation e33d5834-8a48-4355-9176-e71c1d9995f0 · outbound

This paper cites Signal region combination with full and simplified likelihoods in MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Signal region combination with full and simplified likelihoods in MadAnalysis 5

Reference 1

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Observation b07e0f15-6444-4489-992a-1bf6cc78408b · outbound

This paper cites Recasting LHC searches for long-lived particles with MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Recasting LHC searches for long-lived particles with MadAnalysis 5

Reference 2

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Observation a3fc451f-8f28-454d-ab21-336a84a8f963 · outbound

This paper cites Simplified fast detector simulation in MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Simplified fast detector simulation in MadAnalysis 5

Reference 3

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Observation 75f3d381-1269-41ca-a386-ab9796f926b4 · outbound

This paper cites Confronting new physics theories to LHC data with MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Confronting new physics theories to LHC data with MadAnalysis 5

Reference 4

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Observation 593b71cc-1087-40fb-b4bd-e2320e7972b4 · outbound

This paper cites Towards a public analysis database for LHC new physics searches using MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Towards a public analysis database for LHC new physics searches using MadAnalysis 5

Reference 5

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Observation 79d8430a-eede-46e0-9a78-ea0883b58bb7 · outbound

This paper cites Designing and recasting LHC analyses with MadAnalysis 5.

Communicating Likelihoods with Normalising Flows Designing and recasting LHC analyses with MadAnalysis 5

Reference 6

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Observation f812f97c-4074-4c7a-b8c2-1f06152727bb · outbound

This paper cites MadAnalysis 5, a user-friendly framework for collider phenomenology.

Communicating Likelihoods with Normalising Flows MadAnalysis 5, a user-friendly framework for collider phenomenology

Reference 7

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Observation 28d8fe84-e3ee-437b-81b5-5aa15f3d89c0 · outbound

This paper cites Searches for new physics with boosted top quarks in the MadAnalysis 5 and Rivet frameworks.

Communicating Likelihoods with Normalising Flows Searches for new physics with boosted top quarks in the MadAnalysis 5 and Rivet frameworks

Reference 8

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Observation 30664e76-2332-46aa-b6e7-f5c4da0c64e3 · outbound

This paper cites Robust Independent Validation of Experiment and Theory: Rivet version 3.

Communicating Likelihoods with Normalising Flows Robust Independent Validation of Experiment and Theory: Rivet version 3

Reference 9

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Observation 920a4b30-8b27-4d4e-8ee4-6f63e15f5c80 · outbound

This paper cites Fast simulation of detector effects in Rivet.

Communicating Likelihoods with Normalising Flows Fast simulation of detector effects in Rivet

Reference 10

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Observation d08678c5-081e-48b2-9c7b-eaee36c09487 · outbound

This paper cites Rivet user manual.

Communicating Likelihoods with Normalising Flows Rivet user manual

Reference 11

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Observation e65c7813-1473-463b-9458-dc36ffab4df7 · outbound

This paper cites Constraining new physics with SModelS version 2.

Communicating Likelihoods with Normalising Flows Constraining new physics with SModelS version 2

Reference 12

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Observation 14bb95de-4aa5-48bc-b2c8-3dc37a3e3f06 · outbound

This paper cites A SModelS interface for pyhf likelihoods.

Communicating Likelihoods with Normalising Flows A SModelS interface for pyhf likelihoods

Reference 13

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Observation a2870022-b64d-49af-be90-991d3a375e62 · outbound

This paper cites SModelS v1.2: long-lived particles, combination of signal regions, and other novelties.

Communicating Likelihoods with Normalising Flows SModelS v1.2: long-lived particles, combination of signal regions, and other novelties

Reference 14

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Observation bfe68b6e-6c14-4adb-8746-fdc29a02b798 · outbound

This paper cites Cern open data project,.

Communicating Likelihoods with Normalising Flows Cern open data project,

Reference 15

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Observation d6e57307-105e-447c-9c21-b407a5c667bd · outbound

This paper cites Ntuple Wizard: An Application to Access Large-Scale Open Data from LHCb.

Communicating Likelihoods with Normalising Flows Ntuple Wizard: An Application to Access Large-Scale Open Data from LHCb

Reference 16

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Observation a555fee5-0500-4f29-8b85-a1d8928bb43c · outbound

This paper cites Heinrich, M.

Communicating Likelihoods with Normalising Flows Heinrich, M

Reference 17

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Observation e0fb9526-abfe-40d4-88c6-2d94a4b7e682 · outbound

This paper cites Cranmer, G.

Communicating Likelihoods with Normalising Flows Cranmer, G

Reference 18

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Observation a25746ed-2361-46f7-8c40-22ad4c1d4394 · outbound

This paper cites Spey: smooth inference for reinterpretation studies.

Communicating Likelihoods with Normalising Flows Spey: smooth inference for reinterpretation studies

Reference 19

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Observation edcdabf2-dab6-4e37-a00e-4e0d622c0aa4 · outbound

This paper cites Revisiting the Global Electroweak Fit of the Standard Model and Beyond with Gfitter.

Communicating Likelihoods with Normalising Flows Revisiting the Global Electroweak Fit of the Standard Model and Beyond with Gfitter

Reference 20

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Observation ab754310-3fdc-4ce8-8157-0cfb78910bb2 · outbound

This paper cites Higgs coupling measurements at the LHC.

Communicating Likelihoods with Normalising Flows Higgs coupling measurements at the LHC

Reference 21

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Observation 180d4603-f794-4ece-8392-4bfbbeb23f74 · outbound

This paper cites Higgs characterisation in the presence of theoretical uncertainties and invisible decays.

Communicating Likelihoods with Normalising Flows Higgs characterisation in the presence of theoretical uncertainties and invisible decays

Reference 22

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Observation 09a3b488-4e90-418c-ac4b-e17143f776a1 · outbound

This paper cites CheckMATE: Confronting your Favourite New Physics Model with LHC Data.

Communicating Likelihoods with Normalising Flows CheckMATE: Confronting your Favourite New Physics Model with LHC Data

Reference 23

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Observation 6501dac1-132c-44c6-897c-5df2ebf6b802 · outbound

This paper cites CheckMATE 2: From the model to the limit.

Communicating Likelihoods with Normalising Flows CheckMATE 2: From the model to the limit

Reference 24

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Observation 3abe947e-501d-4bb9-9c4b-390389883d9f · outbound

This paper cites GAMBIT: The Global and Modular Beyond-the-Standard-Model Inference Tool.

Communicating Likelihoods with Normalising Flows GAMBIT: The Global and Modular Beyond-the-Standard-Model Inference Tool

Reference 25

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Observation 87913753-b014-4b88-8300-d22bc94999b2 · outbound

This paper cites LHC Constraints on a $B-L$ Gauge Model using Contur.

Communicating Likelihoods with Normalising Flows LHC Constraints on a $B-L$ Gauge Model using Contur

Reference 26

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Observation 158a3de5-dde9-4c6b-8739-23e9d9b79856 · outbound

This paper cites The DNNLikelihood: enhancing likelihood distribution with Deep Learning.

Communicating Likelihoods with Normalising Flows The DNNLikelihood: enhancing likelihood distribution with Deep Learning

Reference 27

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Observation 0d3a9d56-935b-42fc-8c3b-1f9f134aa654 · outbound

This paper cites The NFLikelihood: an unsupervised DNNLikelihood from Normalizing Flows.

Communicating Likelihoods with Normalising Flows The NFLikelihood: an unsupervised DNNLikelihood from Normalizing Flows

Reference 28

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Observation ef342618-f4e2-4ba7-b166-96fcd1e5b5fb · outbound

This paper cites Testable Likelihoods for Beyond-the-Standard Model Fits.

Communicating Likelihoods with Normalising Flows Testable Likelihoods for Beyond-the-Standard Model Fits

Reference 29

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Observation 00a10855-de40-4d11-9b5e-0996806675c9 · outbound

This paper cites Learning Optimal Test Statistics in the Presence of Nuisance Parameters.

Communicating Likelihoods with Normalising Flows Learning Optimal Test Statistics in the Presence of Nuisance Parameters

Reference 30

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Observation 0c944116-c56e-40f1-a60d-d436c051c9cc · outbound

This paper cites Differentiable Vertex Fitting for Jet Flavour Tagging.

Communicating Likelihoods with Normalising Flows Differentiable Vertex Fitting for Jet Flavour Tagging

Reference 31

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Observation 2d0d8256-a8e8-407c-a747-e7cde89af1da · outbound

This paper cites New directions for surrogate models and differentiable programming for High Energy Physics detector simulation.

Communicating Likelihoods with Normalising Flows New directions for surrogate models and differentiable programming for High Energy Physics detector simulation

Reference 32

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Observation 96d334ec-a21c-41f7-81d6-782df03a884d · outbound

This paper cites MadNIS -- Neural Multi-Channel Importance Sampling.

Communicating Likelihoods with Normalising Flows MadNIS -- Neural Multi-Channel Importance Sampling

Reference 33

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This paper cites Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics.

Communicating Likelihoods with Normalising Flows Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics

Reference 34

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This paper cites Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics.

Communicating Likelihoods with Normalising Flows Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics

Reference 35

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This paper cites Finetuning Foundation Models for Joint Analysis Optimization.

Communicating Likelihoods with Normalising Flows Finetuning Foundation Models for Joint Analysis Optimization

Reference 36

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Communicating Likelihoods with Normalising Flows The MadNIS Reloaded

Reference 37

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Communicating Likelihoods with Normalising Flows Differentiable MadNIS-Lite

Reference 38

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Communicating Likelihoods with Normalising Flows The frontier of simulation-based inference

Reference 39

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Communicating Likelihoods with Normalising Flows MadMiner: Machine learning-based inference for particle physics

Reference 40

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This paper cites A Guide to Constraining Effective Field Theories with Machine Learning.

Communicating Likelihoods with Normalising Flows A Guide to Constraining Effective Field Theories with Machine Learning

Reference 41

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Communicating Likelihoods with Normalising Flows Constraining Effective Field Theories with Machine Learning

Reference 42

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This paper cites Constraining the Higgs Potential with Neural Simulation-based Inference for Di-Higgs Production.

Communicating Likelihoods with Normalising Flows Constraining the Higgs Potential with Neural Simulation-based Inference for Di-Higgs Production

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Communicating Likelihoods with Normalising Flows Flow Matching for Scalable Simulation-Based Inference

Reference 44

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Communicating Likelihoods with Normalising Flows Unresolved cited work

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Communicating Likelihoods with Normalising Flows Unresolved cited work

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Communicating Likelihoods with Normalising Flows Flowjax: Distributions and normalizing flows in jax,

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Communicating Likelihoods with Normalising Flows Kidger and C

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Communicating Likelihoods with Normalising Flows JAX: com- posable transformations of Python+NumPy programs,

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Communicating Likelihoods with Normalising Flows Papamakarios, T

Reference 50

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Communicating Likelihoods with Normalising Flows Unresolved cited work

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Communicating Likelihoods with Normalising Flows Neural Spline Flows

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Communicating Likelihoods with Normalising Flows Adam: A Method for Stochastic Optimization

Reference 53

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Communicating Likelihoods with Normalising Flows Kolmogorov–smirnov test,

Reference 54

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Communicating Likelihoods with Normalising Flows Atlas omnifold 24-dimensional z+jets open data,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:21:45.565547Z

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This paper cites A simultaneous unbinned differential cross section measurement of twenty-four $Z$+jets kinematic observables with the ATLAS detector.

Communicating Likelihoods with Normalising Flows A simultaneous unbinned differential cross section measurement of twenty-four $Z$+jets kinematic observables with the ATLAS detector

Reference 56

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Communicating Likelihoods with Normalising Flows Aaij et al

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This paper cites EOS/DATA-2023-01: Supplementary material for EOS/ANALYSIS-2022-05,.

Communicating Likelihoods with Normalising Flows EOS/DATA-2023-01: Supplementary material for EOS/ANALYSIS-2022-05,

Reference 58

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b3af207d-e4e8-4f1f-9496-3a51b0d3ce40 · outbound

This paper cites Toward a complete description of $b \to u \ell^- \bar\nu$ decays within the Weak Effective Theory.

Communicating Likelihoods with Normalising Flows Toward a complete description of $b \to u \ell^- \bar\nu$ decays within the Weak Effective Theory

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T21:21:44.493947Z

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Observation 37676567-55ed-4654-b3c6-acb3dbbeb67c · outbound

This paper cites EOS -- A Software for Flavor Physics Phenomenology.

Communicating Likelihoods with Normalising Flows EOS -- A Software for Flavor Physics Phenomenology

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T21:21:44.499421Z

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Observation 2d5c9663-156f-4644-b039-3a25abd41386 · outbound

This paper cites Constraining $|V_{cs}|$ and physics beyond the Standard Model from exclusive (semi)leptonic charm decays.

Communicating Likelihoods with Normalising Flows Constraining $|V_{cs}|$ and physics beyond the Standard Model from exclusive (semi)leptonic charm decays

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T21:21:44.504770Z

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Observation a72b0dda-f77e-4a53-a98e-0e6a87fc74e8 · outbound

This paper cites Towards a Global Analysis of the $b\to c\bar{u} q$ Puzzle.

Communicating Likelihoods with Normalising Flows Towards a Global Analysis of the $b\to c\bar{u} q$ Puzzle

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T21:21:44.509874Z

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Pith citing papers

Observation e6d99507-1a0a-4818-9c73-5aff180e637a · inbound

Toward an event-level analysis of hadron structure using differential programming cites this paper.

Toward an event-level analysis of hadron structure using differential programming Communicating Likelihoods with Normalising Flows

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:29:54.543101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.