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Paper Citation Record · LEDGER

Toward an event-level analysis of hadron structure using differential programming

As of 7 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2507.15768.

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pith.paper-citation-record.v1
2507.15768 v1

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Outbound references

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This paper cites , K}.(8) 6 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(4×4) 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(4×4) + MH 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(50×50) FIG.

Toward an event-level analysis of hadron structure using differential programming , K}.(8) 6 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(4×4) 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(4×4) + MH 0.2 0.4 0.6 0.8 x 0.2 0.4 0.6 0.8 y LOITS(50×50) FIG

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Toward an event-level analysis of hadron structure using differential programming Unresolved cited work

Reference 2

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Toward an event-level analysis of hadron structure using differential programming , Lfor all theksegments, i.e

Reference 3

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Toward an event-level analysis of hadron structure using differential programming Unresolved cited work

Reference 4

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This paper cites xθ = LI(u;X k, Yk(θ)).(13) Here,X k, Yk(θ) represent the subgrid and corre- sponding local CDF values.

Toward an event-level analysis of hadron structure using differential programming xθ = LI(u;X k, Yk(θ)).(13) Here,X k, Yk(θ) represent the subgrid and corre- sponding local CDF values

Reference 5

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Toward an event-level analysis of hadron structure using differential programming half-moon

Reference 6

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This paper cites A multidimensional unfolding method based on bayes’ theorem,.

Toward an event-level analysis of hadron structure using differential programming A multidimensional unfolding method based on bayes’ theorem,

Reference 7

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Toward an event-level analysis of hadron structure using differential programming Factorization of Hard Processes in QCD

Reference 8

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Toward an event-level analysis of hadron structure using differential programming First Monte Carlo global analysis of nucleon transversity with lattice QCD constraints

Reference 9

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Toward an event-level analysis of hadron structure using differential programming Confronting lattice parton distributions with global QCD analysis

Reference 10

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This paper cites New results in the CTEQ-TEA global analysis of parton distributions in the nucleon.

Toward an event-level analysis of hadron structure using differential programming New results in the CTEQ-TEA global analysis of parton distributions in the nucleon

Reference 11

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Toward an event-level analysis of hadron structure using differential programming First global QCD analysis of the TMD $\boldsymbol{g_{1T}}$ from semi-inclusive DIS data

Reference 12

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Toward an event-level analysis of hadron structure using differential programming Combination of aN$^3$LO PDFs and implications for Higgs production cross-sections at the LHC

Reference 13

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Toward an event-level analysis of hadron structure using differential programming Global QCD analysis of spin PDFs in the proton with high-xand lattice constraints,

Reference 16

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Toward an event-level analysis of hadron structure using differential programming NNLO Global Analysis of Polarized Parton Distribution Functions

Reference 17

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Toward an event-level analysis of hadron structure using differential programming Pion Fragmentation Functions at High Energy Colliders

Reference 18

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Toward an event-level analysis of hadron structure using differential programming Bayesian Inferring Nucleon's Gravitation Form Factors via Near-threshold $J/\psi$ Photoproduction

Reference 19

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Toward an event-level analysis of hadron structure using differential programming Determination of unpolarized TMD distributions from the fit of Drell-Yan and SIDIS data at N 4LL,

Reference 21

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Toward an event-level analysis of hadron structure using differential programming NNPDFpol2.0: a global determination of polarised PDFs and their uncertainties at next-to-next-to-leading order

Reference 23

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Toward an event-level analysis of hadron structure using differential programming Machine Learning in Nuclear Physics

Reference 25

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Toward an event-level analysis of hadron structure using differential programming Presenting Unbinned Differential Cross Section Results

Reference 26

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Toward an event-level analysis of hadron structure using differential programming Unbinned inclusive cross-section measurements with machine-learned systematic uncertainties,

Reference 27

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Toward an event-level analysis of hadron structure using differential programming Optimal binning of X-ray spectra and response matrix design

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Toward an event-level analysis of hadron structure using differential programming INFERNO: Inference-Aware Neural Optimisation

Reference 29

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Toward an event-level analysis of hadron structure using differential programming PDE-Foam - a probability-density estimation method using self-adapting phase-space binning

Reference 30

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Toward an event-level analysis of hadron structure using differential programming Constraining Effective Field Theories with Machine Learning

Reference 32

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Toward an event-level analysis of hadron structure using differential programming The frontier of simulation-based inference

Reference 33

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Toward an event-level analysis of hadron structure using differential programming Constraining the Higgs Potential with Neural Simulation-based Inference for Di-Higgs Production

Reference 35

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Toward an event-level analysis of hadron structure using differential programming QCD Theory meets Information Theory,

Reference 36

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Toward an event-level analysis of hadron structure using differential programming Generator Based Inference (GBI)

Reference 37

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Toward an event-level analysis of hadron structure using differential programming Matching NLO QCD computations with Parton Shower simulations: the POWHEG method

Reference 38

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Toward an event-level analysis of hadron structure using differential programming NNLO jet production in neutral and charged current polarized deep inelastic scattering

Reference 40

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Toward an event-level analysis of hadron structure using differential programming PARTONS: PARtonic Tomography Of Nucleon Software. A computing framework for the phenomenology of Generalized Parton Distributions

Reference 41

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Toward an event-level analysis of hadron structure using differential programming Study of deeply virtual Compton scattering at the future Electron-Ion Collider

Reference 42

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Toward an event-level analysis of hadron structure using differential programming MILOU : a Monte-Carlo for Deeply Virtual Compton Scattering

Reference 43

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Observation dee80d2c-8c94-40cf-8836-15a92f51cd96 · outbound

This paper cites The dipole model Monte Carlo generator Sartre 1.

Toward an event-level analysis of hadron structure using differential programming The dipole model Monte Carlo generator Sartre 1

Reference 44

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Observation 34c57429-6d42-4c18-8de4-f689bcf69ab8 · outbound

This paper cites Exclusive vector meson production at an electron-ion collider.

Toward an event-level analysis of hadron structure using differential programming Exclusive vector meson production at an electron-ion collider

Reference 45

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source=pdf_text observed=2026-08-06T15:29:52.650167Z digest=sha256:fdf7ca2d6c6868a890e10d0be8551cebfb78afdc6af1dc2e3d8852fab31ceb88

Observation 7f735ee6-72ec-4e36-914d-30ab9fc39364 · outbound

This paper cites $\Upsilon$ photo-production on the proton at the Electron-Ion Collider.

Toward an event-level analysis of hadron structure using differential programming $\Upsilon$ photo-production on the proton at the Electron-Ion Collider

Reference 46

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Observation 8fcefaea-43d1-47e4-b46c-e0ff39c9a045 · outbound

This paper cites Invertible Networks or Partons to Detector and Back Again.

Toward an event-level analysis of hadron structure using differential programming Invertible Networks or Partons to Detector and Back Again

Reference 47

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Observation aac8a96b-dca7-4dbc-beee-3cf68d94d919 · outbound

This paper cites Morphing parton showers with event derivatives.

Toward an event-level analysis of hadron structure using differential programming Morphing parton showers with event derivatives

Reference 48

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Observation 38c89430-e693-4257-9061-89e76b7e0246 · outbound

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

Toward an event-level analysis of hadron structure using differential programming MadNIS -- Neural Multi-Channel Importance Sampling

Reference 49

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Observation 12359bfb-094b-4e9d-9e98-d855a56b96c9 · outbound

This paper cites Interpretable deep learning models for the inference and classification of LHC data.

Toward an event-level analysis of hadron structure using differential programming Interpretable deep learning models for the inference and classification of LHC data

Reference 50

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Observation f5a4a2c0-161e-49d8-9ed3-948a5dbc3fba · outbound

This paper cites Fitting a Deep Generative Hadronization Model.

Toward an event-level analysis of hadron structure using differential programming Fitting a Deep Generative Hadronization Model

Reference 51

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Observation 9803e8a8-f777-4f3a-9f48-938765241c68 · outbound

This paper cites Accurate Surrogate Amplitudes with Calibrated Uncertainties,.

Toward an event-level analysis of hadron structure using differential programming Accurate Surrogate Amplitudes with Calibrated Uncertainties,

Reference 52

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Observation da2ce848-80cb-4bdd-a156-05e2923ff9e3 · outbound

This paper cites Differentiable MadNIS-Lite.

Toward an event-level analysis of hadron structure using differential programming Differentiable MadNIS-Lite

Reference 53

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

This paper cites Communicating Likelihoods with Normalising Flows.

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

Reference 54

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Observation 7b8fdc32-c640-4de9-bac5-559ab7e84503 · outbound

This paper cites Unfolding with Generative Adversarial Networks.

Toward an event-level analysis of hadron structure using differential programming Unfolding with Generative Adversarial Networks

Reference 56

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Observation fc1de196-5e9e-4afa-8bae-38446769c8cf · outbound

This paper cites How to GAN away Detector Effects.

Toward an event-level analysis of hadron structure using differential programming How to GAN away Detector Effects

Reference 57

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Observation b3458c20-14ba-4b4b-885e-b93b7bec4fca · outbound

This paper cites Learning to Simulate High Energy Particle Collisions from Unlabeled Data.

Toward an event-level analysis of hadron structure using differential programming Learning to Simulate High Energy Particle Collisions from Unlabeled Data

Reference 58

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Observation a16678b7-a316-4e6c-b88b-e4e8eb0414d2 · outbound

This paper cites Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.

Toward an event-level analysis of hadron structure using differential programming Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference

Reference 59

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Observation d7bc2a84-995c-4686-b8d1-3ad5f7d41b3d · outbound

This paper cites An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training.

Toward an event-level analysis of hadron structure using differential programming An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

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Observation 0497231c-8d45-4929-bfe8-d98a748f69d6 · outbound

This paper cites Unifying Simulation and Inference with Normalizing Flows.

Toward an event-level analysis of hadron structure using differential programming Unifying Simulation and Inference with Normalizing Flows

Reference 61

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Observation 7b50b317-8ec8-44ff-8c45-39b652bafc4b · outbound

This paper cites Improving generative model-based unfolding with Schr¨ odinger bridges,.

Toward an event-level analysis of hadron structure using differential programming Improving generative model-based unfolding with Schr¨ odinger bridges,

Reference 62

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Observation 1dcfac4d-a21f-40d9-a917-d837006e46e7 · outbound

This paper cites Moment Unfolding.

Toward an event-level analysis of hadron structure using differential programming Moment Unfolding

Reference 63

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source=pdf_text observed=2026-08-06T15:29:53.373942Z digest=sha256:82be5bf41c93a5365bf62b8c2b8e5eb4f8e1631bea8fc1375adace5478ac1a12

Observation 2a4f93cd-d8aa-45bf-aa20-bf9e6b6003ad · outbound

This paper cites Generative Unfolding with Distribution Mapping.

Toward an event-level analysis of hadron structure using differential programming Generative Unfolding with Distribution Mapping

Reference 64

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Observation 4734f650-9fee-45a2-bb8a-c5875e39646c · outbound

This paper cites How to Unfold Top Decays.

Toward an event-level analysis of hadron structure using differential programming How to Unfold Top Decays

Reference 65

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Observation 158e4cfa-463c-483c-81ea-dab93eaa41ce · outbound

This paper cites OmniFold: A Method to Simultaneously Unfold All Observables.

Toward an event-level analysis of hadron structure using differential programming OmniFold: A Method to Simultaneously Unfold All Observables

Reference 66

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Observation be7b3542-c141-4ad6-b851-a0e2dded3dce · outbound

This paper cites Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution.

Toward an event-level analysis of hadron structure using differential programming Scaffolding Simulations with Deep Learning for High-dimensional Deconvolution

Reference 67

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Observation d8d46552-4e5a-4f93-860c-fe11d94ac00a · outbound

This paper cites SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory.

Toward an event-level analysis of hadron structure using differential programming SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory

Reference 68

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Observation 9ae3a399-4bc2-4f4b-bb46-d4c52474a6a0 · outbound

This paper cites Tools for Unbinned Unfolding.

Toward an event-level analysis of hadron structure using differential programming Tools for Unbinned Unfolding

Reference 69

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Observation 08be1c6e-8bd3-4c70-bf07-ebc55aecc7d2 · outbound

This paper cites High-Dimensional Unfolding in Large Backgrounds.

Toward an event-level analysis of hadron structure using differential programming High-Dimensional Unfolding in Large Backgrounds

Reference 70

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Observation 232eb385-a4a4-4cc3-8e39-82c10e2a8610 · outbound

This paper cites CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation,.

Toward an event-level analysis of hadron structure using differential programming CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation,

Reference 74

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Observation 46401279-2a82-4d9b-8595-090b6b00f580 · outbound

This paper cites Unbinned Inference with Correlated Events,.

Toward an event-level analysis of hadron structure using differential programming Unbinned Inference with Correlated Events,

Reference 75

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Observation b979c58e-ff00-4843-ac60-38f913d05be8 · outbound

This paper cites Bayesian Approach to Inverse Problems: an Application to NNPDF Closure Testing.

Toward an event-level analysis of hadron structure using differential programming Bayesian Approach to Inverse Problems: an Application to NNPDF Closure Testing

Reference 77

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Observation d965e71d-9920-4ebc-8e90-d9492535bd12 · outbound

This paper cites New Generation of Parton Distributions with Uncertainties from Global QCD Analysis.

Toward an event-level analysis of hadron structure using differential programming New Generation of Parton Distributions with Uncertainties from Global QCD Analysis

Reference 78

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Observation 514fa61b-60d2-4bdd-837a-f454bcf8eec7 · outbound

This paper cites First Monte Carlo analysis of fragmentation functions from single-inclusive $e^+ e^-$ annihilation.

Toward an event-level analysis of hadron structure using differential programming First Monte Carlo analysis of fragmentation functions from single-inclusive $e^+ e^-$ annihilation

Reference 80

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Observation 4fc49457-50db-4065-a78f-b938b916e5b8 · outbound

This paper cites Deeply Virtual Compton Scattering.

Toward an event-level analysis of hadron structure using differential programming Deeply Virtual Compton Scattering

Reference 82

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source=pdf_text observed=2026-08-06T15:29:53.444105Z digest=sha256:1efb810284ecbc4fdacb4f6cc9d4b43a1e0db90b23fd3895d69484124b2ac34b

Observation 76327628-2148-4e94-993d-34e8f30fbfa4 · outbound

This paper cites Unraveling hadron structure with generalized parton distributions.

Toward an event-level analysis of hadron structure using differential programming Unraveling hadron structure with generalized parton distributions

Reference 83

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source=pdf_text observed=2026-08-06T15:29:53.449040Z digest=sha256:2183c60e224d118903095388846fa7c66c2fd3f2c16773bf0f9e7545da779cf3

Observation 50862f21-92bc-40b3-8620-1f94753d5f0b · outbound

This paper cites Kernel methods for evolution of generalized parton distributions.

Toward an event-level analysis of hadron structure using differential programming Kernel methods for evolution of generalized parton distributions

Reference 84

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source=pdf_text observed=2026-08-06T15:29:53.454818Z digest=sha256:2b598a5f61eb4b25e5e252eab9591f07f800868ec1212a54511cf1e4ca4ac9fb

Observation 24c717c2-8ec7-4ae1-8290-f0cf67fa79df · outbound

This paper cites Code for prompt numerical computation of the leading order GPD evolution.

Toward an event-level analysis of hadron structure using differential programming Code for prompt numerical computation of the leading order GPD evolution

Reference 85

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Observation ad2b46a7-be2a-4fee-a1ad-28c2988ae371 · outbound

This paper cites Revisiting evolution equations for generalised parton distributions.

Toward an event-level analysis of hadron structure using differential programming Revisiting evolution equations for generalised parton distributions

Reference 86

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Observation bd2facb9-8c01-42fc-97c9-54ff22884655 · outbound

This paper cites The deconvolution problem of deeply virtual Compton scattering.

Toward an event-level analysis of hadron structure using differential programming The deconvolution problem of deeply virtual Compton scattering

Reference 87

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source=pdf_text observed=2026-08-06T15:29:53.470107Z digest=sha256:159aa2934cc9bd54acdb53a4f64ba130f916aab8ba151f718bdfd826c5ba242f

Observation 760aabe4-6c4a-4391-9bb2-017655a6762c · outbound

This paper cites Shedding light on shadow generalized parton distributions.

Toward an event-level analysis of hadron structure using differential programming Shedding light on shadow generalized parton distributions

Reference 88

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source=pdf_text observed=2026-08-06T15:29:53.475562Z digest=sha256:4e2cc9939e9f92e45af1219cc2c8fb681fdb02f8a85c08aa965a668d8b554768

Observation a7cbdd81-2427-4bb9-8ef7-84bf7d5092ad · outbound

This paper cites Extraction of the Parton Momentum-Fraction Dependence of Generalized Parton Distributions from Exclusive Photoproduction.

Toward an event-level analysis of hadron structure using differential programming Extraction of the Parton Momentum-Fraction Dependence of Generalized Parton Distributions from Exclusive Photoproduction

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This paper cites Flow-based generative models for Markov chain Monte Carlo in lattice field theory.

Toward an event-level analysis of hadron structure using differential programming Flow-based generative models for Markov chain Monte Carlo in lattice field theory

Reference 91

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Observation cffe32bf-f136-4e18-a9d7-259dca8bc299 · outbound

This paper cites Resampling base distributions of normalizing flows,.

Toward an event-level analysis of hadron structure using differential programming Resampling base distributions of normalizing flows,

Reference 92

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Observation 9282113b-abe7-4226-a05e-9ce4879b805b · outbound

This paper cites Accelerating Markov Chain Monte Carlo sampling with diffusion models.

Toward an event-level analysis of hadron structure using differential programming Accelerating Markov Chain Monte Carlo sampling with diffusion models

Reference 93

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Observation e45c3bcd-5b30-4a32-8c02-3734c1b1752f · outbound

This paper cites Generative adversarial nets,.

Toward an event-level analysis of hadron structure using differential programming Generative adversarial nets,

Reference 94

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Observation 7f4e25a8-cefb-420b-a4ed-3766590a349c · outbound

This paper cites SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver.

Toward an event-level analysis of hadron structure using differential programming SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver

Reference 95

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Observation 4136d5c3-efd4-4a73-a588-538eac5cf082 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Toward an event-level analysis of hadron structure using differential programming Adam: A Method for Stochastic Optimization

Reference 96

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