4 papers
Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Framework
Rajesh Shrestha, Xiao Fu
While score-based generative models have emerged as powerful priors for solving inverse problems, directly integrating them into optimization algorithms such as ADMM remains nontri…
Rethinking Coupled Tensor Analysis for Hyperspectral Super-Resolution: Recoverable Modeling Under Endmember Variability
Meng Ding, Xiao Fu
This work revisits the hyperspectral super-resolution (HSR) problem, i.e., fusing a pair of spatially co-registered hyperspectral (HSI) and multispectral (MSI) images to recover a…
Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability
Hoang-Son Nguyen, Xiao Fu
Latent component identification from unknown nonlinear mixtures is a foundational challenge in machine learning, with applications in tasks such as disentangled representation lear…
Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Framework
Yuening Li, Xiao Fu, Junbin Liu +1
This work proposes a variational inference (VI) framework for hyperspectral unmixing in the presence of endmember variability (HU-EV). An EV-accounted noisy linear mixture model (L…