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Neural Networks

11300 directly classified papers

Papers per year

Papers

DeepFlow: Large Displacement Optical Flow with Deep Matching ICCV 2013
Noise-Enhanced Associative Memories NIPS 2013
Image Segmentation with Cascaded Hierarchical Models and Logistic Disjunctive Normal Networks ICCV 2013
Multi-stage Contextual Deep Learning for Pedestrian Detection ICCV 2013
Group Sparsity and Geometry Constrained Dictionary Learning for Action Recognition from Depth Maps ICCV 2013
Hybrid Deep Learning for Face Verification ICCV 2013
Deep Fisher Networks for Large-Scale Image Classification NIPS 2013
Training and Analysing Deep Recurrent Neural Networks NIPS 2013
Multi-Prediction Deep Boltzmann Machines NIPS 2013
Capacity of strong attractor patterns to model behavioural and cognitive prototypes NIPS 2013
Efficient Learning of Simplices COLT 2013
Perfect Associative Learning with Spike-Timing-Dependent Plasticity NIPS 2013
RNADE: The real-valued neural autoregressive density-estimator NIPS 2013
Adaptive dropout for training deep neural networks NIPS 2013
Compete to Compute NIPS 2013
On the Representational Efficiency of Restricted Boltzmann Machines NIPS 2013
Predicting Parameters in Deep Learning NIPS 2013
A Deep Architecture for Matching Short Texts NIPS 2013
Top-Down Regularization of Deep Belief Networks NIPS 2013
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream NIPS 2013
Locally-Linear Learning Machines (L3M) ACML 2013
Distributed Representations of Words and Phrases and their Compositionality NIPS 2013
Learning word embeddings efficiently with noise-contrastive estimation NIPS 2013
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine ACML 2013
Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs NIPS 2013