Jiaqi, Ying, Brian Chaboyer, Phillip A. Cargile, Wenxin Du, George Dufresne

We present the Dartmouth Stellar Evolution Emulator (DSEE), a flow-based stellar evolution model emulator trained on a comprehensive database comprising over eight million evolutionary tracks that vary across twenty input-physics dimensions and span broad ranges in mass and composition. DSEE learns phase-conditioned stellar state snapshots, unifying track and isochrone construction as marginals of one generative model. It delivers continuous interpolation across high-dimensional physics, probabilistic predictions with calibrated credible intervals, and orders-of-magnitude speedups over direct modeling. Validation against current stellar evolution models shows high fidelity across the HR diagrams, while distributional tests recover the full distributions obtained from brute-force Monte Carlo sampling. To broaden impact, DSEE is integrated into the open-source CONF1DENCE package, enabling fast, end-to-end creation of stellar tracks and isochrones. CONF1DENCE includes the ability to make uncertainty-aware age determinations for clusters taking into account observational effects. CONF1DENCE replaces bespoke, fixed-physics grids with a generative, physics-marginalized emulator, setting a practical new standard for stellar modeling and enabling survey-scale analyses with rigorous uncertainty.