Neural Networks

Learning to Pass Expectation Propagation Messages NeurIPS 2013 Learning word embeddings efficiently with noise-contrastive estimation NeurIPS 2013 Locally-Linear Learning Machines (L3M) ACML 2013 Maxout Networks ICML 2013 Multi-Prediction Deep Boltzmann Machines NeurIPS 2013 Multi-stage Contextual Deep Learning for Pedestrian Detection ICCV 2013 Noise-Enhanced Associative Memories NeurIPS 2013 On the Representational Efficiency of Restricted Boltzmann Machines NeurIPS 2013 Perfect Associative Learning with Spike-Timing-Dependent Plasticity NeurIPS 2013 Predicting Parameters in Deep Learning NeurIPS 2013 Reasoning With Neural Tensor Networks for Knowledge Base Completion NeurIPS 2013 Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problems NeurIPS 2013 RNADE: The real-valued neural autoregressive density-estimator NeurIPS 2013 Rotation, Scaling and Deformation Invariant Scattering for Texture Discrimination CVPR 2013 SCaLE: Supervised and Cascaded Laplacian Eigenmaps for Visual Object Recognition Based on Nearest Neighbors CVPR 2013 Shufflets: Shared Mid-level Parts for Fast Object Detection ICCV 2013 Sparse Activity and Sparse Connectivity in Supervised Learning JMLR 2013 Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs NeurIPS 2013 Supervised Sparse Analysis and Synthesis Operators NeurIPS 2013 Top-Down Regularization of Deep Belief Networks NeurIPS 2013 Training and Analysing Deep Recurrent Neural Networks NeurIPS 2013 Understanding Dropout NeurIPS 2013 3D Object Detection and Viewpoint Estimation with a Deformable 3D Cuboid Model NeurIPS 2012 A Better Way to Pretrain Deep Boltzmann Machines NeurIPS 2012 A dynamic excitatory-inhibitory network in a VLSI chip for spiking information reregistrations NeurIPS 2012