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Network model
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171	Under review as a conference paper at ICLRT HE G OLDILOCKS P RINCIPLE : R EADING C HILDREN ’ S B OOKS WITH E XPLICIT M EMORY R EPRESENTATIONS arXiv:1511.02301v3 [cs.CL] 5 Jan 2016 Add to Reading List Source URL: arxiv.org Language: English - Date: 2016-01-06 22:26:21 Cognitive science Cognition Neuropsychology Semantic memory Semantics Memory Artificial neural network Speech recognition Short-term memory Language model Recall Encoding
172	Multiplicative Attribute Graph Model of Real-World Networks Add to Reading List Source URL: i.stanford.edu Language: English - Date: 2013-08-25 23:54:27 Graph theory Networks Network theory Mathematics Discrete mathematics Community structure Degree distribution Node Random graphs Network Homophily
173	Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons Lars Buesing¤, Johannes Bill, Bernhard Nessler, Wolfgang Maass Institute for Theoretical Computer Science, Graz U Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English* - Date: 2014-10-13 19:51:17 Neuroscience Computational neuroscience Nervous system Biology Artificial neural network Biological neuron model Spiking neural network Neural oscillation Gibbs sampling Action potential Neuron Stochastic process
174	Genome Informatics 15(2): 121–Inference of Gene Regulatory Networks by Means of Dynamic Diﬀerential Bayesian Networks and Add to Reading List Source URL: www.jsbi.org Language: English - Date: 2004-12-20 01:20:02 Statistics Econometrics Statistical models Statistical theory Estimation theory Regression analysis Parametric model Linear regression Bayesian network
175	STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES R. C. van Dalen, J. Yang, H. Wang, A. Ragni, C. Zhang, M. J. F. Gales Department of Engineering, University of Cambridge, United Kingdom ABSTRACT State- Add to Reading List Source URL: mi.eng.cam.ac.uk Language: English - Date: 2016-07-12 11:46:12 Markov models Machine learning Artificial intelligence Learning Computational linguistics Speech recognition software Computer accessibility Speech recognition Hidden Markov model Conditional random field Language model Image segmentation
176	Clustered factor analysis of multineuronal spike data Lars Buesing1 , Timothy A. Machado1,2 , John P. Cunningham1 and Liam Paninski1 1 Department of Statistics, Center for Theoretical Neuroscience & Grossman Center for Add to Reading List Source URL: www.gatsby.ucl.ac.uk Language: English - Date: 2014-10-13 19:51:15 Statistics Applied mathematics Machine learning Cluster analysis Cybernetics Dimension reduction Computational neuroscience Mixture model K-means clustering Expectationmaximization algorithm Principal component analysis Artificial neural network
177	BIRDNEST: Bayesian Inference for Ratings-Fraud Detection Bryan Hooi∗ Neil Shah∗ Mohit Kumar§ Add to Reading List Source URL: alexbeutel.com Language: English - Date: 2016-05-18 18:10:27 Statistics Probability Mathematical analysis Probability distributions Dirichlet-multinomial distribution Dirichlet distribution Mixture model Bayesian network Recommender system Multinomial distribution Bayesian inference Markov chain
178	Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves Add to Reading List Source URL: ijcai.org Language: English - Date: 2016-02-13 07:15:40 Artificial intelligence Computational neuroscience Artificial neural networks Applied mathematics Cognitive science Machine learning Cybernetics Model selection Convolutional neural network Hyperparameter optimization Deep learning MNIST database
179	DIGITAL TERRAIN MODELS There were two Digital Terrain Model sessions. "Both of these sessions were chaired by Raymond J. Helmering of the Defense Mapping Agency. Thomas K. Peucker, Robert J. Fowler and James J. Little Add to Reading List Source URL: mapcontext.com Language: English - Date: 2008-08-29 23:37:25 Cartography Geography Triangulated irregular network Digital elevation model Physical geography Planetary science Terrain
180	Parallel Computing–1295 www.elsevier.com/locate/parco Geocomputation’s future at the extremes: high performance computing and nanoclients K.C. Clarke Add to Reading List Source URL: www.geog.ucsb.edu Language: English - Date: 2011-04-27 15:37:35 Concurrent computing Computing Computer architecture Parallel computing Distributed computing architecture Ubiquitous computing Distributed computing Clientserver model Wireless sensor network Thin client Computer cluster Supercomputer