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Description
🚀 Feature Request
Problem: numerical stability for some simulators
Sometimes, SBI gets stuck because of some numerical instability.
Solution
Implements a logit transformation on the conditioning variable bounded within a given interval (min_val, max_val), mapping it to the real line (-inf, inf). This transformation is useful for normalizing bounded data while ensuring numerical stability.
Instead of z_scoring the conditioning variable, one can now also logit-transform it. Allowing in some cases, a more stable evaluation with the rejection-sampling algorithm (if normalized posterior is required).
📌 Additional Context
I have had these issues before with SBI, and implementing a logit transformation helped resolve the numerical instabilities when working in low-data modes.
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enhancementNew feature or requestNew feature or request