PosteriorBench: better reconstruction accuracy can mean worse posterior recovery
AnimaAnandkumar · x · 2026-09-24
Anima Anandkumar's team introduces PosteriorBench, moving evaluation for scientific inverse problems beyond point reconstruction to full posterior distributions.
- Many scientific problems involve indirect or partial observations; multiple physical fields can explain the same measurements, so reconstruction accuracy alone is misleading
- The team spent substantial compute building high-fidelity reference posteriors for four tasks: Darcy flow inversion, Poisson source recovery, carbon capture and storage, and light transport material inference
- Five complementary metrics let researchers directly evaluate their solvers
- Key finding: better reconstruction accuracy can coincide with worse posterior recovery; even strong generative samplers struggle to get both mean and variance right, often underestimating uncertainty
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