Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios
hep-ph, cs.LG, hep-ex, physics.data-an
Submitted: 2026-09-28
Updated: 2026-09-28
Code: https://github.com/taehyounpark/MCFM-10.3
Terminology
Sources
- Approximating Likelihood Ratios with Calibrated Discriminative Classifiers
- The frontier of simulation-based inference
- Neural Simulation-Based Inference of the Neutron Star Equation of State directly from Telescope Spectra
- Real-time gravitational-wave science with neural posterior estimation
- SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering
- A Guide to Constraining Effective Field Theories with Machine Learning
- An implementation of neural simulation-based inference for parameter estimation in ATLAS
- Measurement of off-shell Higgs boson production in the $H^*\rightarrow ZZ\rightarrow 4\ell$ decay channel using a neural simulation-based inference technique in 13 TeV $pp$ collisions with the ATLAS detector
- Neural simulation-based inference of the Higgs trilinear self-coupling via off-shell Higgs production
- MadMiner: Machine learning-based inference for particle physics
- Frequentist Uncertainties on Neural Density Ratios with wifi Ensembles
- Design and performance of the LHCb trigger and full real-time reconstruction in Run 2 of the LHC
- Enriching the physics program of the CMS experiment via data scouting and data parking
- Deep Sets
- Hierarchical Neural Simulation-Based Inference Over Event Ensembles
- It Just Takes Two: Scaling Amortized Inference to Large Sets
- INFERNO: Inference-Aware Neural Optimisation
- neos: End-to-End-Optimised Summary Statistics for High Energy Physics
- Optimal statistical inference in the presence of systematic uncertainties using neural network optimization based on binned Poisson likelihoods with nuisance parameters
- Optimal observables and phase-space ambiguities
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