102 citations · 133 across the 3 of their papers we have counts for
4 papers
Deep regularization and direct training of the inner layers of Neural Networks with Kernel Flows
Gene Ryan Yoo, Houman Owhadi
We introduce a new regularization method for Artificial Neural Networks (ANNs) based on Kernel Flows (KFs). KFs were introduced as a method for kernel selection in regression/krigi…
Kernel Mode Decomposition and programmable/interpretable regression networks
Houman Owhadi, Clint Scovel, Gene Ryan Yoo
Mode decomposition is a prototypical pattern recognition problem that can be addressed from the (a priori distinct) perspectives of numerical approximation, statistical inference a…
Kernel Flows: from learning kernels from data into the abyss
Houman Owhadi, Gene Ryan Yoo
Learning can be seen as approximating an unknown function by interpolating the training data. Kriging offers a solution to this problem based on the prior specification of a kernel…
De-noising by thresholding operator adapted wavelets
Gene Ryan Yoo, Houman Owhadi
Donoho and Johnstone proposed a method from reconstructing an unknown smooth function from noisy data by translating the empirical wavelet coefficients of towards z…