Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI
Leander Thiele
Adrian E. Bayer
Naoya Takeishi

Main:4 Pages
4 Figures
Bibliography:2 Pages
Abstract
The simulation cost for cosmological simulation-based inference can be decreased by combining simulation sets of varying fidelity. We propose an approach to such multi-fidelity inference based on feature matching and knowledge distillation. Our method results in improved posterior quality, particularly for small simulation budgets and difficult inference problems.
View on arXiv@article{thiele2025_2507.00514, title={ Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI }, author={ Leander Thiele and Adrian E. Bayer and Naoya Takeishi }, journal={arXiv preprint arXiv:2507.00514}, year={ 2025 } }
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