mlsanityData to 7 Oct 2026

Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI

arXiv 2507.00514 ↗First posted 1 Jul 2025astro-ph.CO cs.LGcited by 1

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 33 references that are in the map. First posted on arXiv 1 Jul 2025.

Builds on

16 of 33 references.

References · 16

  1. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  2. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
  3. 2019Neural Spline Flowscited by 590
  4. 2019The frontier of simulation-based inferencecited by 490
  5. 2016Revisiting Classifier Two-Sample Testscited by 258
  6. 2018Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flowscited by 217
  7. 2019Automatic Posterior Transformation for Likelihood-Free Inferencecited by 216
  8. 2017Flexible statistical inference for mechanistic models of neural dynamicscited by 162
  9. 2021Benchmarking Simulation-Based Inferencecited by 160
  10. 2018Likelihood-free inference with emulator networkscited by 61
  11. 2021Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimationcited by 13
  12. 2025Multifidelity Simulation-based Inference for Computationally Expensive Simulatorscited by 9
4 more
  1. 2024Simulation-Based Inference with Quantile Regressioncited by 4
  2. 2025Transfer learning for multifidelity simulation-based inference in cosmologycited by 4
  3. 2024Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulatorscited by 2
  4. 2025How many simulations do we need for simulation-based inference in cosmology?cited by 2

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025Transfer Learning Beyond the Standard Modelcited by 0