9 citations · 13 across the 6 of their papers we have counts for
11 papers
Plug-and-Play Image Restoration with Flow Matching: A Continuous Viewpoint
Fan Jia, Yuhao Huang, Shih-Hsin Wang +3
Flow matching-based generative models have been integrated into the plug-and-play image restoration framework, and the resulting plug-and-play flow matching (PnP-Flow) model has ac…
Deep Parameter Interpolation for Scalar Conditioning
Chicago Y. Park, Michael T. McCann, Cristina Garcia-Cardona +2
We propose deep parameter interpolation (DPI), a general-purpose method for transforming an existing deep neural network architecture into one that accepts an additional scalar inp…
A General Framework for Group Sparsity in Hyperspectral Unmixing Using Endmember Bundles
Gokul Bhusal, Yifei Lou, Cristina Garcia-Cardona +1
Due to low spatial resolution, hyperspectral data often consists of mixtures of contributions from multiple materials. This limitation motivates the task of hyperspectral unmixing…
Plug-and-Play Priors as a Score-Based Method
Chicago Y. Park, Yuyang Hu, Michael T. McCann +3
Plug-and-play (PnP) methods are extensively used for solving imaging inverse problems by integrating physical measurement models with pre-trained deep denoisers as priors. Score-ba…
Random Walks with Tweedie: A Unified View of Score-Based Diffusion Models
Chicago Y. Park, Michael T. McCann, Cristina Garcia-Cardona +2
We present a concise derivation for several influential score-based diffusion models that relies on only a few textbook results. Diffusion models have recently emerged as powerful…
A cross-study analysis of drug response prediction in cancer cell lines
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash +21
To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm deve…