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Neural Networks

11300 directly classified papers

Papers per year

Papers

NEUROSVM: An Architecture to Reduce the Effect of the Choice of Kernel on the Performance of SVM JMLR 2009
Conditional Neural Fields NIPS 2009
Unsupervised feature learning for audio classification using convolutional deep belief networks NIPS 2009
On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NIPS 2009
Code-specific policy gradient rules for spiking neurons NIPS 2009
Manifold Learning: The Price of Normalization JMLR 2008
Natural Image Denoising with Convolutional Networks NIPS 2008
Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning NIPS 2008
Self-organization using synaptic plasticity NIPS 2008
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing NIPS 2008
Tracking Changing Stimuli in Continuous Attractor Neural Networks NIPS 2008
Dependence of Orientation Tuning on Recurrent Excitation and Inhibition in a Network Model of V1 NIPS 2008
Short-Term Depression in VLSI Stochastic Synapse NIPS 2008
The Recurrent Temporal Restricted Boltzmann Machine NIPS 2008
Diffeomorphic Dimensionality Reduction NIPS 2008
A Scalable Hierarchical Distributed Language Model NIPS 2008
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks NIPS 2008
Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons NIPS 2008
Generative versus discriminative training of RBMs for classification of fMRI images NIPS 2008
Deep Learning with Kernel Regularization for Visual Recognition NIPS 2008
Implicit Mixtures of Restricted Boltzmann Machines NIPS 2008
Unconstrained On-line Handwriting Recognition with Recurrent Neural Networks NIPS 2007
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NIPS 2007
Sparse deep belief net model for visual area V2 NIPS 2007
Subspace-Based Face Recognition in Analog VLSI NIPS 2007