Tangent Bundle Convolutional Learning: From Manifolds to Cellular Sheaves and Back-Reference-Cited by-同舟云学术

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Tangent Bundle Convolutional Learning: From Manifolds to Cellular Sheaves and Back

Published:2024 Issue: Volume:72 Page:1892-1909
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Battiloro Claudio¹^ORCID,Wang Zhiyang²^ORCID,Riess Hans³^ORCID,Di Lorenzo Paolo⁴^ORCID,Ribeiro Alejandro²^ORCID

Affiliation:

1. Biostatistics Department, Harvard University, Boston, MA, USA

2. Electrical and Systems Engineering Department, University of Pennsylvania, Philadelphia, PA, USA

3. Electronics and Communication Engineering Department, Duke University, Durham, NC, USA

4. Information Engineering, Electronics, and Telecommunications Department, Sapienza University of Rome, Rome, Italy

Funder

NSF CCF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/78/10347386/10476636-aam.pdf

Reference61 articles.

1. Tangent Bundle Filters and Neural Networks: From Manifolds to Cellular Sheaves and Back

2. Gradient-based learning applied to document recognition

3. ImageNet classification with deep convolutional neural networks

4. Applying Convolutional Neural Networks concepts to hybrid NN-HMM model for speech recognition

5. Machine Learning in Social Networks

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