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Neural Networks

11300 directly classified papers

Papers per year

Papers

Shallow vs. Deep Sum-Product Networks NIPS 2011
Sequence learning with hidden units in spiking neural networks NIPS 2011
Learning to Learn with Compound HD Models NIPS 2011
Selecting Receptive Fields in Deep Networks NIPS 2011
Mixed-Variate Restricted Boltzmann Machines ACML 2011
Robust Generation of Dynamical Patterns in Human Motion by a Deep Belief Nets ACML 2011
The Neural Autoregressive Distribution Estimator AISTATS 2011
Deep Sparse Rectifier Neural Networks AISTATS 2011
Deep Learners Benefit More from Out-of-Distribution Examples AISTATS 2011
Learning Class-relevant Features and Class-irrelevant Features via a Hybrid third-order RBM AISTATS 2011
Variational Learning for Recurrent Spiking Networks NIPS 2011
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm NIPS 2011
Kernel Analysis of Deep Networks JMLR 2011
The Kernel Beta Process NIPS 2011
Why The Brain Separates Face Recognition From Object Recognition NIPS 2011
Two Distributed-State Models For Generating High-Dimensional Time Series JMLR 2011
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation JMLR 2010
Short-term memory in neuronal networks through dynamical compressed sensing NIPS 2010
Inferring Stimulus Selectivity from the Spatial Structure of Neural Network Dynamics NIPS 2010
Deep Coding Network NIPS 2010
SpikeAnts, a spiking neuron network modelling the emergence of organization in a complex system NIPS 2010
Tiled convolutional neural networks NIPS 2010
Layer-wise analysis of deep networks with Gaussian kernels NIPS 2010
A biologically plausible network for the computation of orientation dominance NIPS 2010
Learning Convolutional Feature Hierarchies for Visual Recognition NIPS 2010