PIS: A Generalized Physical Inversion Solver for Sparse Observations Using Diffusion Models
Published:Dec 14, 2025 06:28
•1 min read
•ArXiv
Analysis
This research introduces a novel approach to solve physical inversion problems using set-conditioned diffusion models, potentially advancing the field of inverse problem solving. The paper's focus on sparse observations suggests an attempt to address real-world data limitations, which could be impactful.
Key Takeaways
Reference
“PIS is a Generalized Physical Inversion Solver for Arbitrary Sparse Observations via Set-Conditioned Diffusion.”