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Neural Networks

629 directly classified papers

Papers per year

Papers

General Stochastic Networks for Classification NIPS 2014
A Machine Learning Approach for Non-blind Image Deconvolution CVPR 2013
Deep Learning Identity-Preserving Face Space ICCV 2013
Learning Stochastic Feedforward Neural Networks NIPS 2013
Capacity of strong attractor patterns to model behavioural and cognitive prototypes NIPS 2013
Firing rate predictions in optimal balanced networks NIPS 2013
Fully-Connected CRFs with Non-Parametric Pairwise Potential CVPR 2013
A Neural Autoregressive Topic Model NIPS 2012
Analog readout for optical reservoir computers NIPS 2012
ImageNet Classification with Deep Convolutional Neural Networks NIPS 2012
Deep Neural Networks Segment Neuronal Membranes in Electron Microscopy Images NIPS 2012
A Hybrid Neural Network-Latent Topic Model AISTATS 2012
Deep Boltzmann Machines as Feed-Forward Hierarchies AISTATS 2012
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm NIPS 2011
In All Likelihood, Deep Belief Is Not Enough JMLR 2011
Variational Learning for Recurrent Spiking Networks NIPS 2011
A Spike and Slab Restricted Boltzmann Machine AISTATS 2011
Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model NIPS 2010
Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images AISTATS 2010
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines AISTATS 2010
A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration NIPS 2010
Code-specific policy gradient rules for spiking neurons NIPS 2009
A Neural Implementation of the Kalman Filter NIPS 2009
Kernel Methods for Deep Learning NIPS 2009
Tracking Changing Stimuli in Continuous Attractor Neural Networks NIPS 2008