{"total":13,"rows":[{"id":"2411.00446","title":"A Lorentz-Equivariant Transformer for All of the LHC","created":"2024-11-01","cited_by_count":28,"area":null},{"id":"2404.18807","title":"The Landscape of Unfolding with Machine Learning","created":"2024-04-29","cited_by_count":20,"area":null},{"id":"2404.14332","title":"Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion","created":"2024-04-22","cited_by_count":8,"area":null},{"id":"2404.18992","title":"Unifying Simulation and Inference with Normalizing Flows","created":"2024-04-29","cited_by_count":6,"area":null},{"id":"2411.02495","title":"Generative Unfolding with Distribution Mapping","created":"2024-11-04","cited_by_count":6,"area":null},{"id":"2601.13308","title":"Scaling laws for amplitude surrogates","created":"2026-01-19","cited_by_count":6,"area":null},{"id":"2507.15084","title":"Simulation-Prior Independent Neural Unfolding Procedure","created":"2025-07-20","cited_by_count":4,"area":null},{"id":"2410.10216","title":"Neural Quasiprobabilistic Likelihood Ratio Estimation with Negatively Weighted Data","created":"2024-10-14","cited_by_count":2,"area":null},{"id":"2412.12074","title":"Extrapolating Jet Radiation with Autoregressive Transformers","created":"2024-12-16","cited_by_count":2,"area":null},{"id":"2605.02014","title":"MIRA: A Score for Conditional Distribution Accuracy and Model Comparison","created":"2026-05-03","cited_by_count":1,"area":null},{"id":"2512.07074","title":"Machine Learning-based Unfolding for Cross Section Measurements in the Presence of Nuisance Parameters","created":"2025-12-08","cited_by_count":0,"area":null},{"id":"2601.22029","title":"Inverse Problems Conditioned on Observation Ensembles: Applications and Methods","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2604.01313","title":"ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics","created":"2026-04-01","cited_by_count":0,"area":null}],"next_cursor":null}