aurelio-amerio/GenSBI
Generative Models for Simulation-Based Inference in JAX
Implements Optimal Transport Conditional Flow Matching and Diffusion Models for posterior inference when likelihoods are intractable. Built on JAX and Flax NNX with support for CPUs, GPUs, and TPUs, it includes pre-built transformer architectures (Flux1, Simformer) and a high-level recipes API for streamlined training and sampling workflows.
Available on PyPI.
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Language
Python
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Last pushed
Mar 16, 2026
Monthly downloads
128
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0
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17
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