Difference between revisions of "GP SSM"

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(Papers on Deep Learning)
(Papers on Deep Learning)
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* Soatto Paper
 
* Soatto Paper
 
* P. Chauderi, A.Oberman, S. Osher, S. Soatto, G. Ccarlier, [[Media:DeepNetPDEs.pdf | Deep Relaxation: Partial Differential Equations for Optimizing Deep Neural Networks]], ''arXiV:1704.04932v2''
 
* P. Chauderi, A.Oberman, S. Osher, S. Soatto, G. Ccarlier, [[Media:DeepNetPDEs.pdf | Deep Relaxation: Partial Differential Equations for Optimizing Deep Neural Networks]], ''arXiV:1704.04932v2''
 +
* A. Achile and S. Soatto, [[Media:InvarianceDisentanglement.pdf | Emergence of Invariance and Disentanglement in Deep Representations]], ''arXiV:1706.01350v2'', Oct. 2017.
  
 
=== Web Links ===
 
=== Web Links ===

Revision as of 17:57, 16 January 2018

This page gathers references and materials related to the study of

  • Gaussian Process (GP) State Space Models (SSM)
  • Deep Learning
  • Koopman Spectral Methods.

Gaussian Process Approaches

Basic Gaussian Process Info

  • Rasmussen and Williams

Web Links

Papers on GP-SSMs


Deep Learning

Papers on Deep Learning

Web Links

Koopman Spectral Method

Papers on Koopman Spectral methods

Papers which are more oriented toward control

Papers which are more oriented toward fluids

Some Early Papers

Other Papers