12 citations · 14 across the 7 of their papers we have counts for
3 papers · 1 filter
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…
Are We Really Learning the Score Function? Reinterpreting Diffusion Models Through Wasserstein Gradient Flow Matching
An B. Vuong, Michael T. McCann, Javier E. Santos +1
Diffusion models are commonly interpreted as learning the score function, i.e., the gradient of the log-density of noisy data. However, this assumption implies that the target of l…
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…