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Neural networks
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151	Presented at AAAI-16 conference, February 12-17, 2016, Phoenix, Arizona USA Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks ´ ska and Ingmar Posner Peter Ondruˇ Mobile Robotics Group, University of Add to Reading List Source URL: www.robots.ox.ac.uk - Date: 2016-02-12 18:04:19
152	Longitudinal Analysis of Discussion Topics in an Online Breast Cancer Community using Convolutional Neural Networks Shaodian Zhang1 , Edouard Grave1 , Elizabeth Sklar2 and No´emie Elhadad1 1 Columbia University, New Yor Add to Reading List Source URL: arxiv.org - Date: 2016-04-07 21:05:45
153	Deep Taylor Decomposition of Neural Networks Gr´egoire Montavon1 Sebastian Bach2 Alexander Binder3 Wojciech Samek2,5 Add to Reading List Source URL: icmlviz.github.io - Date: 2016-07-22 05:35:28
154	Analyzing and Validating Neural Networks Predictions Alexander Binder1 Wojciech Samek2,5 Gr´egoire Montavon3 Sebastian Bach2 Add to Reading List Source URL: icmlviz.github.io - Date: 2016-07-22 05:35:28
155	Neural networks Feedforward neural network - multilayer neural network ARTIFICIAL NEURON 1 Add to Reading List Source URL: dl.dropboxusercontent.com
156	ISSCCSESSION 14 / NEXT-GENERATION PROCESSINGEyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks Add to Reading List Source URL: www.rle.mit.edu - Date: 2016-02-03 01:33:12
157	Inversion of Feedforward Neural Networks: Algorithms and Applications CRAIG A. JENSEN, RUSSELL D. REED, ROBERT J. MARKS, II, FELLOW, IEEE, MOHAMED A. EL-SHARKAWI, FELLOW, IEEE, JAE-BYUNG JUNG, ROBERT T. MIYAMOTO, GREGORY Add to Reading List Source URL: marksmannet.com
158	Neural networks Conditional random fields - factors, sufficient statistics and linear CRF 0) b Add to Reading List Source URL: dl.dropboxusercontent.com
159	Neural networks Training neural networks - parameter gradient P MACHINE LEARNING Add to Reading List Source URL: dl.dropboxusercontent.com
160	Detection and Classification of Acoustic Scenes and EventsSeptember 2016, Budapest, Hungary CP-JKU SUBMISSIONS FOR DCASE-2016: A HYBRID APPROACH USING BINAURAL I-VECTORS AND DEEP CONVOLUTIONAL NEURAL NETWORKS Add to Reading List Source URL: www.cs.tut.fi - Date: 2016-08-30 06:05:43

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