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Principles of riemannian geometry in neural networks
Michael Hauser,
Asok Ray
Mechanical Engineering
Research output
:
Contribution to journal
›
Conference article
›
peer-review
32
Scopus citations
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Dive into the research topics of 'Principles of riemannian geometry in neural networks'. Together they form a unique fingerprint.
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Keyphrases
Neural Network
100%
Riemannian Geometry
100%
Data Manifold
60%
Dynamical Systems
20%
Lie Group Actions
20%
Learning Systems
20%
Coordinate Transformation
20%
System of Differential Equations
20%
Associated Bundle
20%
Geometric Transformation
20%
Metric Tensor
20%
Feedforward Network
20%
Finite Difference Approximation
20%
Principal Bundle
20%
Fiber Spacing
20%
Mathematics
Neural Network
100%
Riemannian Geometry
100%
Manifold
50%
Dynamical System
16%
Residuals
16%
Action (of a Lie Group)
16%
System Of Differential Equations
16%
Finite Difference Method
16%
First order differential equation
16%
Closed Form Solution
16%
Metric Tensor
16%
Fiber Space
16%