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Neural networks
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#	Item
361	A deep-network solution towards model-less obstacle avoidance Lei Tai1 , Shaohua Li2 , Ming Liu1,2 Abstract— Obstacle avoidance is the core problem for mobile robots. Its objective is to allow mobile robots to explore Add to Reading List Source URL: ram-lab.com Language: English - Date: 2016-08-03 06:46:08 Computational neuroscience Artificial intelligence Cybernetics Neuroscience Artificial neural networks Formal sciences Machine learning Computer vision Convolutional neural network Deep learning Robotics Pattern recognition
362	arXiv:1409.3215v3 [cs.CL] 14 Dec 2014 Add to Reading List Source URL: arxiv.org Language: English - Date: 2014-12-15 20:32:58 Artificial neural networks Artificial intelligence Machine learning Computational neuroscience Computational linguistics Cybernetics Artificial intelligence applications Computer-assisted translation Deep learning Long short-term memory Recurrent neural network Speech recognition
363	Your partner for hands-on CNS electrophysiology NSF SET * Add to Reading List Source URL: www.neuroservice.com Language: English - Date: 2014-12-05 07:20:03 Nervous system Neuroscience Neurophysiology Brain Neurology Neural networks Synaptic plasticity Long-term potentiation Hippocampus Schaffer collateral
364	Introduction Model Fitting Neural Networks Add to Reading List Source URL: www.pstat.ucsb.edu Language: English - Date: 2014-11-07 15:19:36 Artificial neural networks Applied mathematics Perceptron Activation function Cellular neural network
365	Fully Autonomous Real-Time Autoencoder-Augmented Hebbian Learning through the Collection of Novel Experiences To appear in: Proc. of the Fifteenth International Conference on the Synthesis and Simulation of Living System Add to Reading List Source URL: eplex.cs.ucf.edu Language: English - Date: 2016-04-27 14:27:24 Computational neuroscience Neuroscience Artificial neural networks Cybernetics Cognition Machine learning Computational statistics Hebbian theory Autoencoder Deep learning Feature learning Unsupervised learning
366	arXiv:1506.00019v4 [cs.LG] 17 OctA Critical Review of Recurrent Neural Networks for Sequence Learning Zachary C. Lipton Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-10-19 21:37:55 Artificial neural networks Cybernetics Applied mathematics Machine learning Recurrent neural network Deep learning Feedforward neural network Long short-term memory Convolutional neural network Backpropagation Connectionism Restricted Boltzmann machine
367	Robert Gordon University, Sir Ian Wood Building Garthdee Road, Aberdeen, AB10 7GJ UK, Scotland Friday 2nd September 2016 Start Time Add to Reading List Source URL: www.eann.org.uk Language: English - Date: 2016-08-11 07:57:24 Artificial neural networks Computational neuroscience Computational statistics Applied mathematics Cybernetics Cognitive science Spiking neural network Deep learning Glenfiddich Machine learning Recurrent neural network Speech recognition
368	Team APL: Intelligent Fusion of CNN Ensembles Christopher M. Gifford, Pedro A. Rodriguez, Ryan Amundsen, Stefan Awad, Brant Chee, Clare Lau, Ajay Patrikar The Johns Hopkins University Applied Physics Laboratory (JHU/APL) Add to Reading List Source URL: image-net.org Language: English - Date: 2015-12-16 23:04:56 Computational neuroscience Artificial intelligence Machine learning Statistical classification Artificial neural networks Cognitive science Learning Computer vision Convolutional neural network Support vector machine Classifier Deep learning
369	Signatures of criticality arise in simple neural population models with correlations Marcel Nonnenmacher1,2,3* , Christian Behrens3,4 , Philipp Berens3,4,5,6 , Matthias Bethge2,3,4 , Jakob H. Macke1,2,3* 1 research cente Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:45 Computational neuroscience Physics Statistics Neuroscience Nervous system Probability distributions Neural networks Computational statistics Neural coding Ising model Biological neuron model Correlation and dependence
370	Self-organizing map in Matlab: the SOM Toolbox Juha Vesanto, Johan Himberg, Esa Alhoniemi and Juha Parhankangas Laboratory of Computer and Information Science, Helsinki University of Technology, Finland Abstract The Sel Add to Reading List Source URL: www.cis.hut.fi Language: English - Date: 2000-10-09 05:53:25 Software Application software Mathematical software Artificial neural networks Array programming languages Machine learning Dimension reduction Self-organizing map Cross-platform software MATLAB Unsupervised learning U-matrix

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