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PtyGenography: using generative models for regularization of the phase retrieval problem
Selin Aslan, Tristan van Leeuwen, Allard Mosk +1
In phase retrieval and similar inverse problems, the stability of solutions across different noise levels is crucial for applications. One approach to promote it is using signal pr…
Efficient uniform approximation using Random Vector Functional Link networks
Palina Salanevich, Olov Schavemaker
A Random Vector Functional Link (RVFL) network is a depth-2 neural network with random inner weights and biases. Only the outer weights of such an architecture are to be learned, s…
Random Vector Functional Link Networks for Function Approximation on Manifolds
Deanna Needell, Aaron A. Nelson, Rayan Saab +2
The learning speed of feed-forward neural networks is notoriously slow and has presented a bottleneck in deep learning applications for several decades. For instance, gradient-base…