2 layer neural networks as Wasserstein gradient flows: Difference between revisions

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==References==
==References==
<references>
<references>
<ref name="Figalli">[https://people.math.ethz.ch/~afigalli/lecture-notes-pdf/The-continuous-formulation-of-shallow-neural-networks-as-wasserstein-type-gradient-flows.pdf Xavier Fernandez-Real and Alessio Figalli, ''The Continuous Formulation of Shallow Neural
<ref name="Figalli">[https://people.math.ethz.ch/~afigalli/lecture-notes-pdf/The-continuous-formulation-of-shallow-neural-networks-as-wasserstein-type-gradient-flows.pdf Xavier Fernandez-Real and Alessio Figalli, ''The Continuous Formulation of Shallow Neural Networks as Wasserstein-Type Gradient Flows'']</ref>
Networks as Wasserstein-Type Gradient Flows'']</ref>




</references>
</references>

Revision as of 01:21, 10 February 2022

[1]

Motivation

Shallow Neural Networks

Continuous Formulation

Minimization Problem

Wasserstein Gradient Flow

Main Results

References

  1. ↑ Xavier Fernandez-Real and Alessio Figalli, The Continuous Formulation of Shallow Neural Networks as Wasserstein-Type Gradient Flows
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