Deep Haar scattering networks

DOI10.1093/imaiai/iaw007zbMath1380.68331arXiv1509.09187OpenAlexW2230873857MaRDI QIDQ4603720

Xiuyuan Cheng, Xu Chen, Stephane Mallat

Publication date: 19 February 2018

Published in: Information and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1509.09187

zbMATH Keywords

neural networkgraphsscattering transformHaar waveletdeep learningclassification images

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (9)

Asymptotic analysis of higher-order scattering transform of Gaussian processes ⋮ Graph Fourier transform based on \(\ell_1\) norm variation minimization ⋮ Understanding Graph Neural Networks with Generalized Geometric Scattering Transforms ⋮ Central and Noncentral Limit Theorems Arising from the Scattering Transform and Its Neural Activation Generalization ⋮ GSNs: generative stochastic networks ⋮ Regularity properties of Haar frames ⋮ On the convergence of formally diverging neural net-based classifiers ⋮ Rotationally invariant time-frequency scattering transforms ⋮ Stability for the training of deep neural networks and other classifiers

Uses Software

• darch
• DeepFace

Cites Work

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• Some deviation inequalities
• Diffusion wavelets
• Group Invariant Scattering
• Harmonic Analysis of Digital Data Bases
• Reducing the Dimensionality of Data with Neural Networks
• An Efficient Implementation of Edmonds' Algorithm for Maximum Matching on Graphs
• Paths, Trees, and Flowers
• A Fast Learning Algorithm for Deep Belief Nets

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