Separation Capacity of Scattering Networks

arXiv:2606.30822 · stat.ML, cs.IT, cs.LG, math.CV · Submitted 2026-06-29 · Read on arXiv

Konstantin Häberle, Helmut Bölcskei

stat.ML, cs.IT, cs.LG, math.CV

Submitted: 2026-06-29

Comments: 36 pages, 10 figures

Code: https://github.com/konstantin-haberle/ScatteringCapacity

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Feature Extraction — 4× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 3× in this paper · explained in 3 episodes
• VC Dimension — 3× in this paper · explained in 2 episodes
• Composition — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 14 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Orthogonal Projection — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 6 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Vector Representations — 1× in this paper · explained in 2 episodes
• Wavelet Transform — 1× in this paper · explained in 2 episodes

Sources

• Scale Dependencies and Self-Similar Models with Wavelet Scattering Spectra

Related papers

• Behavior of prediction performance metrics with rare events
• Optimal Estimation of Generic Dynamics by Path-Dependent Neural Jump ODEs
• A Posterior-Dynamics Framework for Imaging Inverse Problems with Pretrained Diffusion Priors
• Scalable Posterior Uncertainty for Flexible Density-Based Clustering
• A Transport Geometry of Benign Overfitting
• Efficient quadratic entropy with distance sketches