Recent advances in cosmological simulations and observations have highlighted the critical role of baryonic physics in shaping the gas–galaxy–halo connection across a wide range of scales, from cosmic filaments and galaxy groups to massive clusters. The CAMELS and Baryon Pasting (BP) projects represent complementary approaches to modeling these effects, combining controlled simulation suites with flexible, data-driven treatments of baryonic processes.

The CAMELS + Baryon Pasting Workshop aims to bring together experts in simulations, observations, and machine learning to critically assess these approaches, compare modeling assumptions, and identify robust, physically motivated observables. A focus of the workshop is the role of modern machine-learning techniques—particularly simulation-based inference and interpretable ML—in enabling efficient parameter inference while preserving physical interpretability and systematic control. By fostering close interaction among theory, simulation, ML, and observational communities, the workshop seeks to define shared benchmarks and establish a coherent roadmap for next-generation analyses of baryonic effects in cosmology.