A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks ¨ Felix Grun Technische Universit¨at M¨unchen, Germany

First Page		Document Content
Date: 2016-06-23 05:02:01 Artificial neural networks Computational neuroscience Convolutional neural network Backpropagation Artificial intelligence Autoencoder Biological neural network Deep learning Vanishing gradient problem		A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks ¨ Felix Grun Technische Universit¨at M¨unchen, Germany Add to Reading List Source URL: campar.in.tum.de Download Document from Source Website File Size: 4,32 MB Share Document on Facebook

	Syntax-Directed Variational Autoencoder for Molecule Generation Hanjun Dai1* , Yingtao Tian2* , Bo Dai1 , Steven Skiena2 , Le Song1 1 College of Computing, Georgia Institute of Technology 2 DocID: 1vlR1 - View Document
	Semi-Supervised Recursive Autoencoder Si Chen and Yufei Wang Department of Electrical and Computer Engineering University of California San Diego {sic046, yuw176}@ucsd.edu DocID: 1v727 - View Document
	An Autoencoder Approach to Learning Bilingual Word Representations Sarath Chandar A P1 ∗ , Stanislas Lauly2 ∗ , Hugo Larochelle2 , Mitesh M Khapra3 , Balaraman Ravindran1 , Vikas Raykar3 , Amrita Saha3 1 DocID: 1v23p - View Document
	On Nonparametric Guidance for Learning Autoencoder Representations Jasper Snoek University of Toronto DocID: 1uwmD - View Document
	arXiv:1610.00291v1 [cs.CV] 2 OctDeep Feature Consistent Variational Autoencoder Xianxu Hou University of Nottingham, Ningbo China DocID: 1tDNC - View Document