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eess.IV2025
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…
eess.IV2025
An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM
Luke Lozenski, Michael T. McCann, Brendt Wohlberg
This work presents a new method for online selection of multiple penalty parameters for the alternating direction method of multipliers (ADMM) algorithm applied to optimization pro…
eess.IV2024
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…