# sbi reloaded: a toolkit for simulation-based inference workflows

*Source* · `src-boelts-2025-sbi-reloaded` · status: **n/a**

| field | value |
|---|---|
| kind | Preprint |
| authors | Jan Boelts, Michael Deistler, Manuel Gloeckler, et al., Jakob H. Macke |
| date | 2024-11-26 |
| url | https://arxiv.org/abs/2411.17337 |
| arxiv | 2411.17337 |
| accessed | 2026-10-24 |
| notes | PyTorch sbi package: neural posterior, likelihood and ratio estimators, diagnostics, amortized inference; needs only simulator samples, no gradients. |

## Backlinks (computed)

**cited by:** [Simulation-based inference for calibrating simulators](../technique/simulation-based-inference.md)

## Citation

Jan Boelts, Michael Deistler, Manuel Gloeckler, et al., Jakob H. Macke (2024-11-26). *sbi reloaded: a toolkit for simulation-based inference workflows*.  https://arxiv.org/abs/2411.17337

---
Provenance: created in run `2026-10-24-techniques-sim-math`.