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Neural networks
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11	Latte: A Language, Compiler, and Runtime for Elegant and Efficient Deep Neural Networks Leonard Truong Rajkishore Barik Add to Reading List Source URL: thev.net Language: English - Date: 2016-07-05 13:12:15 Artificial neural networks Machine learning Applied mathematics Cybernetics Artificial neuron Backpropagation Recurrent neural network Deep learning Multilayer perceptron Neuron Neural network Perceptron
12	Concolic Testing for Deep Neural Networks Add to Reading List Source URL: qav.comlab.ox.ac.uk Language: English - Date: 2018-08-02 04:45:47
13	SPNs: Network Reconstruction Theory and Speedup Using Neural Networks Balaji Prabhakar and Mendel Rosenblum Self-‐Programming Networks Research Group Stanf Add to Reading List Source URL: platformlab.stanford.edu Language: English - Date: 2018-02-21 18:51:55 Network performance Abstract data types Operations research Concurrency control Monitor Queueing theory Queue Statistical theory Probability and statistics Economy
14	This Talk § 1) Node embeddings § Map nodes to low-dimensional embeddings. § 2) Graph neural networks Add to Reading List Source URL: snap.stanford.edu Language: English - Date: 2018-04-25 02:50:02 Mathematics Algebra Topology Machine learning Artificial neural networks Feature learning Embedding Deep learning Proj construction Kernel embedding of distributions
15	Towards Reverse-Engineering Black-Box Neural Networks Seong Joon Oh Max Augustin Bernt Schiele Add to Reading List Source URL: vision.soic.indiana.edu Language: English - Date: 2018-02-23 06:31:16
16	Deep-Learning: general principles + Convolutional Neural Networks Pr. Fabien Moutarde Center for Robotics MINES ParisTech Add to Reading List Source URL: perso.mines-paristech.fr Language: English - Date: 2018-03-28 11:42:55
17	NLP Programming Tutorial 7 – Neural Networks NLP Programming Tutorial 7 Neural Networks Graham Neubig Nara Institute of Science and Technology (NAIST) Add to Reading List Source URL: www.phontron.com Language: English - Date: 2015-07-13 23:04:51
18	A PDE APPROACH TO REGULARIZATION IN DEEP LEARNING ADAM OBERMAN JOINT WORK WITH CHAUDHARI, OSHER, SOATTO AND CARLIER The fundamental tool for training deep neural networks is Stochastic Gradient Add to Reading List Source URL: cmx.caltech.edu Language: English - Date: 2017-08-28 13:59:57
19	Gated Feedback Recurrent Neural Networks arXiv:1502.02367v4 [cs.NE] 17 Jun 2015 Junyoung Chung Caglar Gulcehre Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-06-17 20:17:05
20	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, VOL. 23, NO. 11, NOVEMBERSemisupervised Classification With Cluster Regularization Add to Reading List Source URL: staff.ustc.edu.cn Language: English - Date: 2014-04-11 09:32:09

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