Generative Amplification with Surrogate Monte Carlo | Paper Citation Record

Observation 38184e54-7bf0-4ce0-96c5-4966f6eaf773 · outbound

This paper cites Calibrating Bayesian Generative Machine Learning for Bayesiamplification.

Generative Amplification with Surrogate Monte Carlo Calibrating Bayesian Generative Machine Learning for Bayesiamplification

Reference 1

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Observation ece72cf9-0910-48d4-8586-cab498be640a · outbound

This paper cites MadSpace -- Event Generation for the Era of GPUs and ML.

Generative Amplification with Surrogate Monte Carlo MadSpace -- Event Generation for the Era of GPUs and ML

Reference 2

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Observation 8d854b79-ca22-42f1-98bd-30e009773d3d · outbound

This paper cites Sampling NNLO QCD phase space with normalizing flows.

Generative Amplification with Surrogate Monte Carlo Sampling NNLO QCD phase space with normalizing flows

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.425537Z

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Observation e6c35cae-f9ad-45b9-87a4-64afe242ece5 · outbound

This paper cites Efficient many-jet event generation with Flow Matching.

Generative Amplification with Surrogate Monte Carlo Efficient many-jet event generation with Flow Matching

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.429405Z

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Observation e1f4e8a5-2c69-429e-a49a-1e8af16743f6 · outbound

This paper cites Madgraph5\_aMC@NLO on GPUs and vector CPUs Experience with the first alpha release.

Generative Amplification with Surrogate Monte Carlo Madgraph5\_aMC@NLO on GPUs and vector CPUs Experience with the first alpha release

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.437052Z

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Observation 1792a705-19aa-4666-b2b7-8356a0759246 · outbound

This paper cites Speeding up Madgraph5 aMC@NLO through CPU vectorization and GPU offloading: towards a first alpha release.

Generative Amplification with Surrogate Monte Carlo Speeding up Madgraph5 aMC@NLO through CPU vectorization and GPU offloading: towards a first alpha release

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.440972Z

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Observation 06d4b682-617d-4fb6-b6b8-feceeb5bad7e · outbound

This paper cites A Portable Parton-Level Event Generator for the High-Luminosity LHC.

Generative Amplification with Surrogate Monte Carlo A Portable Parton-Level Event Generator for the High-Luminosity LHC

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.446008Z

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Observation b68e800c-35b0-4e0d-9f9d-bf8bc21246ad · outbound

This paper cites Accelerating LHC event generation with simplified pilot runs and fast PDFs.

Generative Amplification with Surrogate Monte Carlo Accelerating LHC event generation with simplified pilot runs and fast PDFs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.451090Z

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Observation 6e56dcbf-09c5-4728-8b24-4d4d3ec2a3e8 · outbound

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

Generative Amplification with Surrogate Monte Carlo Branches of a Tree: Taking Derivatives of Programs with Discrete and Branching Randomness in High Energy Physics

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.455975Z

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Observation b17e2b1d-ba45-46b4-a436-7f2e5a4cd484 · outbound

This paper cites MadFlow: automating Monte Carlo simulation on GPU for particle physics processes.

Generative Amplification with Surrogate Monte Carlo MadFlow: automating Monte Carlo simulation on GPU for particle physics processes

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.461757Z

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Observation 1d22572b-552f-4628-8821-2f81eee16028 · outbound

This paper cites and Rossi, Marco.

Generative Amplification with Surrogate Monte Carlo and Rossi, Marco

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.468631Z

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Observation 44af92b8-0558-4e01-b873-8d332c443c15 · outbound

This paper cites Accelerating HEP simulations with Neural Importance Sampling.

Generative Amplification with Surrogate Monte Carlo Accelerating HEP simulations with Neural Importance Sampling

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.473719Z

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Observation b7fabf58-ac9f-4c2c-9f43-3361cccbdcc9 · outbound

This paper cites Unifying Simulation and Inference with Normalizing Flows.

Generative Amplification with Surrogate Monte Carlo Unifying Simulation and Inference with Normalizing Flows

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.479767Z

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Observation 1cf6f88a-6dc9-4f42-afb5-35d71936b5cf · outbound

This paper cites Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows.

Generative Amplification with Surrogate Monte Carlo Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.485157Z

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Observation dd40c7c4-b6af-4fe4-b23e-64ce92ebe20f · outbound

This paper cites PIPPIN: Generating variable length full events from partons.

Generative Amplification with Surrogate Monte Carlo PIPPIN: Generating variable length full events from partons

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.489383Z

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Observation 1ffd0544-830b-4afb-a1ee-36a4a841f8c1 · outbound

This paper cites Toward the end-to-end optimization of particle physics instruments with differentiable programming.

Generative Amplification with Surrogate Monte Carlo Toward the end-to-end optimization of particle physics instruments with differentiable programming

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.493423Z

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Observation c8e92905-10c3-4fe8-b310-1ac629b2c383 · outbound

This paper cites Morphing parton showers with event derivatives.

Generative Amplification with Surrogate Monte Carlo Morphing parton showers with event derivatives

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.497376Z

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Observation 8d000d2b-dc9d-4090-bcd6-2caf511a3b3f · outbound

This paper cites Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations.

Generative Amplification with Surrogate Monte Carlo Optimization Using Pathwise Algorithmic Derivatives of Electromagnetic Shower Simulations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.501761Z

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Observation fb95e06e-3ec7-476c-bc63-5578770b6c32 · outbound

This paper cites The Les Houches Accord PDFs (LHAPDF) and Lhaglue.

Generative Amplification with Surrogate Monte Carlo The Les Houches Accord PDFs (LHAPDF) and Lhaglue

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.505182Z

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Observation 5214b9b0-cf1e-4194-bffe-21b7b06fee49 · outbound

This paper cites Unweighting multijet event generation using factorisation-aware neural networks.

Generative Amplification with Surrogate Monte Carlo Unweighting multijet event generation using factorisation-aware neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.509620Z

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Observation d362d03f-903f-4d56-85e5-a8d195d8c517 · outbound

This paper cites Exploring phase space with Nested Sampling.

Generative Amplification with Surrogate Monte Carlo Exploring phase space with Nested Sampling

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.513973Z

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Observation d941519b-786b-4aa3-baf2-a1d5251b5e38 · outbound

This paper cites Efficient phase-space generation for hadron collider event simulation.

Generative Amplification with Surrogate Monte Carlo Efficient phase-space generation for hadron collider event simulation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.519623Z

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Observation 199e4975-9c99-4090-bc35-6afb0f8026f9 · outbound

This paper cites Event-by-event Comparison between Machine-Learning- and Transfer-Matrix-based Unfolding Methods.

Generative Amplification with Surrogate Monte Carlo Event-by-event Comparison between Machine-Learning- and Transfer-Matrix-based Unfolding Methods

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.526183Z

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Observation fcb1bdd3-a521-4779-8917-e02bf8278e4d · outbound

This paper cites PC-Droid: Faster diffusion and improved quality for particle cloud generation.

Generative Amplification with Surrogate Monte Carlo PC-Droid: Faster diffusion and improved quality for particle cloud generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.531876Z

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Observation 6db2e413-1188-410e-9e16-09fbc78aff5b · outbound

This paper cites $\nu^2$-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows.

Generative Amplification with Surrogate Monte Carlo $\nu^2$-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.536790Z

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Observation 83bc3f36-60db-469f-96ce-7e117e348357 · outbound

This paper cites EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion.

Generative Amplification with Surrogate Monte Carlo EPiC-ly Fast Particle Cloud Generation with Flow-Matching and Diffusion

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.542971Z

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Observation 0fe2e086-3187-4808-85b3-972d37b1344a · outbound

This paper cites Returning CP-Observables to The Frames They Belong.

Generative Amplification with Surrogate Monte Carlo Returning CP-Observables to The Frames They Belong

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.548040Z

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Observation b8fcec1f-3d4d-49cc-bf4b-29d55763264a · outbound

This paper cites SciPost Phys.

Generative Amplification with Surrogate Monte Carlo SciPost Phys

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.553175Z

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Observation d215637c-c464-46b8-82da-c41420f7036a · outbound

This paper cites Machine Learning and LHC Event Generation.

Generative Amplification with Surrogate Monte Carlo Machine Learning and LHC Event Generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.558228Z

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Observation 5fc38e3a-ffc7-4e85-80a0-fdfe985a64ab · outbound

This paper cites Inductive Simulation of Calorimeter Showers with Normalizing Flows.

Generative Amplification with Surrogate Monte Carlo Inductive Simulation of Calorimeter Showers with Normalizing Flows

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.563852Z

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Observation 6453dae8-059d-4c48-a27e-f93fa6a5311b · outbound

This paper cites CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation.

Generative Amplification with Surrogate Monte Carlo CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.568404Z

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Observation 82614742-5df7-403f-8ec7-ef1b04ee22df · outbound

This paper cites EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets.

Generative Amplification with Surrogate Monte Carlo EPiC-GAN: Equivariant Point Cloud Generation for Particle Jets

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.573403Z

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Observation 36c85b37-f58c-4535-9532-fb01ca94771f · outbound

This paper cites SciPost Phys.

Generative Amplification with Surrogate Monte Carlo SciPost Phys

Reference 34

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Observation a365bd01-7276-4d47-8026-f00892d4d854 · outbound

This paper cites Jet Diffusion versus JetGPT -- Modern Networks for the LHC.

Generative Amplification with Surrogate Monte Carlo Jet Diffusion versus JetGPT -- Modern Networks for the LHC

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.581942Z

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Observation d22b0780-ad7b-427d-8fc7-5c7f9781c454 · outbound

This paper cites Comparison of Affine and Rational Quadratic Spline Coupling and Autoregressive Flows through Robust Statistical Tests.

Generative Amplification with Surrogate Monte Carlo Comparison of Affine and Rational Quadratic Spline Coupling and Autoregressive Flows through Robust Statistical Tests

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.585875Z

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Observation 1dabea1b-64c4-4906-9587-1fd43658c02b · outbound

This paper cites How to Understand Limitations of Generative Networks.

Generative Amplification with Surrogate Monte Carlo How to Understand Limitations of Generative Networks

Reference 37

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Observation be7b91e1-d1c4-4181-9210-3349084f9378 · outbound

This paper cites New Angles on Fast Calorimeter Shower Simulation.

Generative Amplification with Surrogate Monte Carlo New Angles on Fast Calorimeter Shower Simulation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.596514Z

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Observation 70117855-8069-47ee-8222-22d11e6275a1 · outbound

This paper cites L2LFlows: Generating High-Fidelity 3D Calorimeter Images.

Generative Amplification with Surrogate Monte Carlo L2LFlows: Generating High-Fidelity 3D Calorimeter Images

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.600889Z

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Observation e87d456d-b096-4e1c-8e68-3d4170fe97b2 · outbound

This paper cites 2308.12351 , archiveprefix =.

Generative Amplification with Surrogate Monte Carlo 2308.12351 , archiveprefix =

Reference 40

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Observation 0322663d-6c14-40c6-8273-c077cd75b57a · outbound

This paper cites Refining Fast Calorimeter Simulations with a Schr\"{o}dinger Bridge.

Generative Amplification with Surrogate Monte Carlo Refining Fast Calorimeter Simulations with a Schr\"{o}dinger Bridge

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.610150Z

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Observation aa9de171-8176-442e-964c-4fc6d5dbe187 · outbound

This paper cites Anomalies, Representations, and Self-Supervision.

Generative Amplification with Surrogate Monte Carlo Anomalies, Representations, and Self-Supervision

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.614832Z

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Observation c308b421-d3c2-44d0-ad0d-c556c9025a75 · outbound

This paper cites Like-Sign W-Boson Scattering at the LHC -- Approximations and Full Next-to-Leading-Order Predictions.

Generative Amplification with Surrogate Monte Carlo Like-Sign W-Boson Scattering at the LHC -- Approximations and Full Next-to-Leading-Order Predictions

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.619518Z

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Observation 7c4baa47-4506-47a7-8696-e86fa6f5786f · outbound

This paper cites 23xx.xxxx , archiveprefix =.

Generative Amplification with Surrogate Monte Carlo 23xx.xxxx , archiveprefix =

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.623563Z

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Observation b533b66a-6dac-4e34-b8d2-7c554a7696f5 · outbound

This paper cites Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning.

Generative Amplification with Surrogate Monte Carlo Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.628658Z

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Observation 2ef23de1-53b7-486e-8023-55ca46971a5c · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 46

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Observation 1fa91bc7-d3ff-4c1c-8ea6-af2c71f7823f · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 47

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Observation 22450cfe-ac22-4399-9680-812762d30bce · outbound

This paper cites PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics.

Generative Amplification with Surrogate Monte Carlo PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.642832Z

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Observation ad8fcd6c-18b8-4c38-8838-46ac88d3c5fd · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 49

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Observation ae806b03-48b9-4187-aba4-052b2ffb773e · outbound

This paper cites One-loop matrix element emulation with factorisation awareness.

Generative Amplification with Surrogate Monte Carlo One-loop matrix element emulation with factorisation awareness

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.651826Z

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Observation afb4d180-2bf8-4f93-98ad-1e829eb21e0c · outbound

This paper cites Fast Point Cloud Generation with Diffusion Models in High Energy Physics.

Generative Amplification with Surrogate Monte Carlo Fast Point Cloud Generation with Diffusion Models in High Energy Physics

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.656914Z

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Observation d584be34-2a70-440a-ba56-dbdbb7524c2e · outbound

This paper cites ELSA -- Enhanced latent spaces for improved collider simulations.

Generative Amplification with Surrogate Monte Carlo ELSA -- Enhanced latent spaces for improved collider simulations

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.660791Z

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Observation 91ed8dbd-a7c4-4600-9583-aef97841d121 · outbound

This paper cites CURTAINs for your Sliding Window: Constructing Unobserved Regions by Transforming Adjacent Intervals.

Generative Amplification with Surrogate Monte Carlo CURTAINs for your Sliding Window: Constructing Unobserved Regions by Transforming Adjacent Intervals

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.664966Z

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Observation 0c34f736-7992-478e-af6a-0086231dfc78 · outbound

This paper cites Learning Likelihood Ratios with Neural Network Classifiers.

Generative Amplification with Surrogate Monte Carlo Learning Likelihood Ratios with Neural Network Classifiers

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.669013Z

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Observation ab8cb0ab-1436-44dd-ac90-70e46815f7ea · outbound

This paper cites CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation.

Generative Amplification with Surrogate Monte Carlo CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.676266Z

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Observation c8360f61-b28f-428b-9775-9192ab975f57 · outbound

This paper cites End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics.

Generative Amplification with Surrogate Monte Carlo End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.683362Z

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Observation 417006af-f9bc-4dab-aa26-c14e2c5654a9 · outbound

This paper cites Generative Machine Learning for Detector Response Modeling with a Conditional Normalizing Flow.

Generative Amplification with Surrogate Monte Carlo Generative Machine Learning for Detector Response Modeling with a Conditional Normalizing Flow

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.688015Z

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Observation 22c7c282-17eb-4ab4-a863-0cd01df4b3a0 · outbound

This paper cites Deep generative models for fast photon shower simulation in ATLAS.

Generative Amplification with Surrogate Monte Carlo Deep generative models for fast photon shower simulation in ATLAS

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.692567Z

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Observation 0eaa45cf-4a5c-45b5-b167-8ce2eab839ff · outbound

This paper cites AtlFast3: the next generation of fast simulation in ATLAS.

Generative Amplification with Surrogate Monte Carlo AtlFast3: the next generation of fast simulation in ATLAS

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.696601Z

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Observation 79d27d19-7e7f-4ad0-8f97-37f3914beebc · outbound

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

Generative Amplification with Surrogate Monte Carlo New directions for surrogate models and differentiable programming for High Energy Physics detector simulation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.700499Z

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Observation 7cd9cd86-7585-44fe-9195-662b007f4581 · outbound

This paper cites Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report.

Generative Amplification with Surrogate Monte Carlo Theory, phenomenology, and experimental avenues for dark showers: a Snowmass 2021 report

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.704489Z

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Observation 235d2204-e939-4af8-8244-f7602142a7d8 · outbound

This paper cites JINST , volume = 17, number =.

Generative Amplification with Surrogate Monte Carlo JINST , volume = 17, number =

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.708416Z

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Observation b97d2e80-9be5-42c6-babe-19310c997b31 · outbound

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

Generative Amplification with Surrogate Monte Carlo An unfolding method based on conditional Invertible Neural Networks (cINN) using iterative training

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.712354Z

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Observation be133b1f-d3fc-4298-8bf8-62d98134ed3b · outbound

This paper cites and Keilbach, Fabian and Plehn, Tilman and Kasieczka, Gregor and Whiteson, Daniel , title =.

Generative Amplification with Surrogate Monte Carlo and Keilbach, Fabian and Plehn, Tilman and Kasieczka, Gregor and Whiteson, Daniel , title =

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.716026Z

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Observation fd5bb8c3-149e-4024-94a2-c7558fca7c59 · outbound

This paper cites Shared Data and Algorithms for Deep Learning in Fundamental Physics.

Generative Amplification with Surrogate Monte Carlo Shared Data and Algorithms for Deep Learning in Fundamental Physics

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.724453Z

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Observation 7cd41e18-5cfb-4816-a715-cdd6e69ff116 · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.728742Z

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Observation c004a530-baee-48c4-bcb2-29984e8199a0 · outbound

This paper cites Comparing Machine Learning and Interpolation Methods for Loop-Level Calculations.

Generative Amplification with Surrogate Monte Carlo Comparing Machine Learning and Interpolation Methods for Loop-Level Calculations

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.734036Z

Source-reported events for the cited work

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Observation af498890-3e05-422c-a57f-526dd275c97d · outbound

This paper cites CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds.

Generative Amplification with Surrogate Monte Carlo CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.740997Z

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Observation f21b517b-a9f0-49de-b7ad-45ebbaf95bfb · outbound

This paper cites Accelerating Monte Carlo event generation -- rejection sampling using neural network event-weight estimates.

Generative Amplification with Surrogate Monte Carlo Accelerating Monte Carlo event generation -- rejection sampling using neural network event-weight estimates

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.745371Z

Source-reported events for the cited work

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Observation 76b48efb-b75c-405b-ae06-e5d175f3c1d4 · outbound

This paper cites Feature Selection with Distance Correlation.

Generative Amplification with Surrogate Monte Carlo Feature Selection with Distance Correlation

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.750411Z

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Observation e1ce4db4-b8a1-49ba-97b0-4ee862e206d2 · outbound

This paper cites and Favaro, Luigi and Plehn, Tilman and Sorrenson, Peter and Kr\"amer, Michael , title =.

Generative Amplification with Surrogate Monte Carlo and Favaro, Luigi and Plehn, Tilman and Sorrenson, Peter and Kr\"amer, Michael , title =

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.755813Z

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Observation 6fd7db0f-2b29-459a-8ff9-a9488066a1be · outbound

This paper cites Symmetries, Safety, and Self-Supervision.

Generative Amplification with Surrogate Monte Carlo Symmetries, Safety, and Self-Supervision

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.760056Z

Source-reported events for the cited work

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Observation 4b362880-814f-49f5-8381-abdb464cbd70 · outbound

This paper cites Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper.

Generative Amplification with Surrogate Monte Carlo Toward the End-to-End Optimization of Particle Physics Instruments with Differentiable Programming: a White Paper

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.764694Z

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Observation a46df479-f630-434b-8213-1d977bf0b03a · outbound

This paper cites Learning Lattice Quantum Field Theories with Equivariant Continuous Flows.

Generative Amplification with Surrogate Monte Carlo Learning Lattice Quantum Field Theories with Equivariant Continuous Flows

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.769865Z

Source-reported events for the cited work

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Observation 865a3557-ab99-44a6-9fe4-22a03624468c · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.774162Z

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Observation a20efb5d-dabf-4ebc-92c3-f38b51c282aa · outbound

This paper cites FETA: Flow-Enhanced Transportation for Anomaly Detection.

Generative Amplification with Surrogate Monte Carlo FETA: Flow-Enhanced Transportation for Anomaly Detection

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.778740Z

Source-reported events for the cited work

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Observation 7e4a703d-cf69-43d1-b02b-1baac1d303e8 · outbound

This paper cites JHEP , volume =.

Generative Amplification with Surrogate Monte Carlo JHEP , volume =

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.783080Z

Source-reported events for the cited work

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Observation ba1d65fb-cf6c-4b5a-ad9d-f851f72bbd74 · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.788141Z

Source-reported events for the cited work

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Observation 6b91e951-b727-4778-97bb-5a18b77d22c0 · outbound

This paper cites Resonant anomaly detection without background sculpting.

Generative Amplification with Surrogate Monte Carlo Resonant anomaly detection without background sculpting

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.791914Z

Source-reported events for the cited work

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Observation d9075ad7-a932-4aa6-8388-23cb16d9534e · outbound

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

Generative Amplification with Surrogate Monte Carlo MadNIS -- Neural Multi-Channel Importance Sampling

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.796181Z

Source-reported events for the cited work

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Observation e9a502ee-da5e-4fb8-bfbc-6df6daed9357 · outbound

This paper cites Differentiable Matrix Elements with MadJax.

Generative Amplification with Surrogate Monte Carlo Differentiable Matrix Elements with MadJax

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.800320Z

Source-reported events for the cited work

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Observation 5566822e-653a-43cb-b5eb-4d2e36c5c21a · outbound

This paper cites CaloFlow for CaloChallenge Dataset 1.

Generative Amplification with Surrogate Monte Carlo CaloFlow for CaloChallenge Dataset 1

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.804145Z

Source-reported events for the cited work

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Observation 9a557c27-1009-4ed3-b3b7-7b435a0f305c · outbound

This paper cites \nu-Flows: Conditional Neutrino Regression.

Generative Amplification with Surrogate Monte Carlo \nu-Flows: Conditional Neutrino Regression

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.809019Z

Source-reported events for the cited work

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Observation e1b1f636-e75a-4e11-b3e4-0e41fc8a9d8d · outbound

This paper cites Multi-variable Integration with a Neural Network.

Generative Amplification with Surrogate Monte Carlo Multi-variable Integration with a Neural Network

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.812877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7effebb-d501-4ff7-8bba-a1694487fe37 · outbound

This paper cites TF07 Snowmass Report: Theory of Collider Phenomena.

Generative Amplification with Surrogate Monte Carlo TF07 Snowmass Report: Theory of Collider Phenomena

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.816745Z

Source-reported events for the cited work

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Observation 3b510fd6-6c74-4e91-9463-1381cf8143cc · outbound

This paper cites Efficiently Moving Instead of Reweighting Collider Events with Machine Learning.

Generative Amplification with Surrogate Monte Carlo Efficiently Moving Instead of Reweighting Collider Events with Machine Learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.821069Z

Source-reported events for the cited work

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Observation 9d25a561-c02f-4207-bcde-f45ffa0b6646 · outbound

This paper cites an unresolved cited work.

Generative Amplification with Surrogate Monte Carlo Unresolved cited work

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.826306Z

Source-reported events for the cited work

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Observation 5b2c5a8b-8875-4a44-bab5-7b43a1f879bf · outbound

This paper cites over, Lennart and Sch\.

Generative Amplification with Surrogate Monte Carlo over, Lennart and Sch\

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.830385Z

Source-reported events for the cited work

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Observation 964d8d0d-5b63-403c-99e5-5e7f5f424d33 · outbound

This paper cites over, Lennart and Sch\.

Generative Amplification with Surrogate Monte Carlo over, Lennart and Sch\

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.834981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5014a52-e82d-467d-8708-944f7441ccf8 · outbound

This paper cites Jets and Jet Substructure at Future Colliders.

Generative Amplification with Surrogate Monte Carlo Jets and Jet Substructure at Future Colliders

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.838775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4379d0eb-211b-41fa-b2c2-8e919ee96e15 · outbound

This paper cites Modern Machine Learning for LHC Physicists.

Generative Amplification with Surrogate Monte Carlo Modern Machine Learning for LHC Physicists

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.843639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb2a1f2a-8523-48f6-aedb-1c0e2e65fb49 · outbound

This paper cites Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning.

Generative Amplification with Surrogate Monte Carlo Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.847928Z

Source-reported events for the cited work

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Observation 4d210ffb-a2aa-4c40-9c23-9df417061827 · outbound

This paper cites SciPost Phys.

Generative Amplification with Surrogate Monte Carlo SciPost Phys

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.852520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08218117-b87b-41b8-bc65-727d6263acf1 · outbound

This paper cites Targeting Multi-Loop Integrals with Neural Networks.

Generative Amplification with Surrogate Monte Carlo Targeting Multi-Loop Integrals with Neural Networks

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.857408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05db30b7-3203-4369-af5b-4091ebf15e6f · outbound

This paper cites Deep-Learning based Reconstruction of the Shower Maximum $X_{\mathrm{max}}$ using the Water-Cherenkov Detectors of the Pierre Auger Observatory.

Generative Amplification with Surrogate Monte Carlo Deep-Learning based Reconstruction of the Shower Maximum $X_{\mathrm{max}}$ using the Water-Cherenkov Detectors of the Pierre Auger Observatory

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.861534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a141d9-f9d8-422b-a995-a4e2ba0bdba7 · outbound

This paper cites The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider.

Generative Amplification with Surrogate Monte Carlo The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron Collider

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.866197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 752ca841-0ae2-4cf7-a46d-c409f4042f8f · outbound

This paper cites Fast convolutional neural networks on FPGAs with hls4ml.

Generative Amplification with Surrogate Monte Carlo Fast convolutional neural networks on FPGAs with hls4ml

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.870075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1a154e4-7049-4d8e-9736-09f6fa004bdb · outbound

This paper cites Wire-Cell 3D Pattern Recognition Techniques for Neutrino Event Reconstruction in Large LArTPCs: Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation.

Generative Amplification with Surrogate Monte Carlo Wire-Cell 3D Pattern Recognition Techniques for Neutrino Event Reconstruction in Large LArTPCs: Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.874044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c38359ee-46f2-4016-ac9a-5f915bc1073a · outbound

This paper cites Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction.

Generative Amplification with Surrogate Monte Carlo Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.878071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1274e9c0-693c-4ddd-a76f-0be17afa91d9 · outbound

This paper cites Electromagnetic Shower Reconstruction and Energy Validation with Michel Electrons and $\pi^0$ Samples for the Deep-Learning-Based Analyses in MicroBooNE.

Generative Amplification with Surrogate Monte Carlo Electromagnetic Shower Reconstruction and Energy Validation with Michel Electrons and $\pi^0$ Samples for the Deep-Learning-Based Analyses in MicroBooNE

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.881963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ff8d16-d14f-478b-be37-4a6bc05445f9 · outbound

This paper cites Search for an anomalous excess of charged-current quasi-elastic $\nu_e$ interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction.

Generative Amplification with Surrogate Monte Carlo Search for an anomalous excess of charged-current quasi-elastic $\nu_e$ interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction

Reference 102

Resolution: unresolved; no resolver link, observed 2026-08-15T14:39:56.887057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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