montefiore-institute/balanced-nre
Code for the paper "Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation".
This project helps scientists and researchers who use complex computer simulations to understand real-world phenomena. It takes your simulation outputs and helps you infer the underlying parameters that produced them, providing more reliable and less overconfident results. This is for anyone who needs to be sure their conclusions from simulation-based models are robust, without risking false inferences due to overly optimistic predictions.
No commits in the last 6 months.
Use this if you conduct simulation-based inference and need to ensure your estimated posteriors are conservative and trustworthy, especially when dealing with limited simulation data.
Not ideal if your primary goal is to maximize computational speed at the cost of potential overconfidence in your simulation-based inference results.
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Language
Jupyter Notebook
License
BSD-3-Clause
Category
Last pushed
Nov 14, 2022
Commits (30d)
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