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Download Bronstein2016geometric, Geometric Deep Learning - Going Beyond Euclidean Data by ['jaweria01'] in PDF format completely FREE. No registration required, no payment needed. Get instant access to this valuable resource on PDFdrive.to!
About Bronstein2016geometric, Geometric Deep Learning - Going Beyond Euclidean Data
This document summarizes key challenges and opportunities in the field of geometric deep learning. It discusses how deep learning has achieved success with Euclidean data like images and speech but faces challenges in applying these methods to non-Euclidean geometric data found in domains like graphics, vision, language processing and biology. The document outlines two classes of geometric learning problems and reviews approaches that have been explored to generalize convolutional neural networks and other deep learning techniques to graphs and manifolds to help unlock their potential for problems involving non-Euclidean data.
Detailed Information
| Author: | ['jaweria01'] |
|---|---|
| Publication Year: | 2017 |
| Pages: | 20 |
| Language: | English |
| Format: | |
| Price: | FREE |
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