devzhk/InverseBench
InverseBench (ICLR 2025 spotlight)
InverseBench helps scientists working with challenging physical data, such as medical images or seismic readings, to accurately reconstruct the original information from incomplete or noisy observations. It takes the observed data and an algorithm choice, then outputs improved reconstructions and detailed performance metrics specific to the scientific domain. This tool is for researchers and practitioners in fields like medical imaging, astronomy, or geophysics who need to evaluate and compare advanced image reconstruction methods.
105 stars.
Use this if you are a scientist or engineer who needs to benchmark and understand the performance of diffusion-prior-based algorithms for inverse problems in physical sciences, like reconstructing black hole images or analyzing fluid dynamics from partial data.
Not ideal if you are looking for a ready-to-use application for general image restoration or if your inverse problem doesn't involve complex scientific data from fields like tomography or seismology.
Stars
105
Forks
12
Language
Python
License
MIT
Category
Last pushed
Feb 10, 2026
Commits (30d)
0
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