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stat.ML2025
Geometric Scattering on Measure Spaces
Joyce Chew, Matthew Hirn, Smita Krishnaswamy +5
The scattering transform is a multilayered, wavelet-based transform initially introduced as a model of convolutional neural networks (CNNs) that has played a foundational role in o…
stat.ML2025
Manifold Filter-Combine Networks
David R. Johnson, Joyce A. Chew, Edward De Brouwer +3
In order to better understand manifold neural networks (MNNs), we introduce Manifold Filter-Combine Networks (MFCNs). Our filter-combine framework parallels the popular aggregate-c…
stat.ML2024
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…