2 citations · 5 across the 20 of their papers we have counts for
4 papers · 1 filter
Measurement Geometry and Design for Trustworthy Generative Inverse Problems
Pengfei Jin, Na Li, Quanzheng Li
Generative models are increasingly used as priors for inverse problems, but their ability to produce realistic images creates a basic trust problem: a plausible reconstruction may…
PIRF: Physics-Informed Reward Fine-Tuning for Diffusion Models
Mingze Yuan, Pengfei Jin, Na Li +1
Diffusion models have demonstrated strong generative capabilities across scientific domains, but often produce outputs that violate physical laws. We propose a new perspective by f…
System-Embedded Diffusion Bridge Models
Bartlomiej Sobieski, Matthew Tivnan, Yuang Wang +5
Solving inverse problems -- recovering signals from incomplete or noisy measurements -- is fundamental in science and engineering. Score-based generative models (SGMs) have recentl…
Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection
Pengfei Jin, Peng Shu, Sifan Song +6
Recent advances in parameter-efficient transfer learning have demonstrated the utility of composing LoRA adapters from libraries of pretrained modules. However, most existing appro…