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Found 2 papers, 1 papers with code
Random ReLU Neural Networks as Non-Gaussian Processes
We prove that these random neural networks are well-defined non-Gaussian processes.
Delaunay-Triangulation-Based Learning with Hessian Total-Variation Regularization
Rectified linear unit (ReLU) neural networks generate continuous and piecewise-linear (CPWL) mappings and are the state-of-the-art approach for solving regression problems.
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