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howpublished = {Deep Learning and Unsupervised Feature Learning NIPS 2012 Workshop},  abstract = {Theano is a linear algebra compiler that optimizes a user’s symbolically-specified mathematical computations to produce efficient low-level implementations. In this paper, we present new features and efficiency improvements to Theano, and benchmarks demonstrating Theano’s performance relative to Torch7, a recently introduced machine learning library, and to RNNLM, a C++ library targeted at recurrent neural networks.},  }  @article{DBLP:journals/corr/SimonyanZ14a,  author = {Karen Simonyan and  Andrew Zisserman}, 
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biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/SimonyanZ14a},  bibsource = {dblp computer science bibliography, http://dblp.org}  }  @article{DBLP:journals/corr/SimonyanVZ13,  author = {Karen Simonyan and  Andrea Vedaldi and  Andrew Zisserman},  title = {Deep Inside Convolutional Networks: Visualising Image Classification  Models and Saliency Maps},  journal = {CoRR},  volume = {abs/1312.6034},  year = {2013},  url = {http://arxiv.org/abs/1312.6034},  timestamp = {Mon, 06 Jan 2014 15:10:41 +0100},  biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/SimonyanVZ13},  bibsource = {dblp computer science bibliography, http://dblp.org}  }