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Neural Networks

11300 directly classified papers

Papers per year

Papers

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks NIPS 2015
Bidirectional Recurrent Neural Networks as Generative Models NIPS 2015
Deep Knowledge Tracing NIPS 2015
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring NIPS 2015
Teaching Machines to Read and Comprehend NIPS 2015
Hessian-free Optimization for Learning Deep Multidimensional Recurrent Neural Networks NIPS 2015
Neural Adaptive Sequential Monte Carlo NIPS 2015
Deep Temporal Sigmoid Belief Networks for Sequence Modeling NIPS 2015
Enforcing balance allows local supervised learning in spiking recurrent networks NIPS 2015
Interactive Control of Diverse Complex Characters with Neural Networks NIPS 2015
Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NIPS 2015
Statistical Model Criticism using Kernel Two Sample Tests NIPS 2015
Associative Memory via a Sparse Recovery Model NIPS 2015
Going Deeper With Convolutions CVPR 2015
Modeling Local and Global Deformations in Deep Learning: Epitomic Convolution, Multiple Instance Learning, and Sliding Window Detection CVPR 2015
Cross-Scene Crowd Counting via Deep Convolutional Neural Networks CVPR 2015
End-to-End Integration of a Convolution Network, Deformable Parts Model and Non-Maximum Suppression CVPR 2015
Understanding Image Representations by Measuring Their Equivariance and Equivalence CVPR 2015
On the Relationship Between Visual Attributes and Convolutional Networks CVPR 2015
Saliency Detection by Multi-Context Deep Learning CVPR 2015
DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection CVPR 2015
Deep LAC: Deep Localization, Alignment and Classification for Fine-Grained Recognition CVPR 2015
Multi-Objective Convolutional Learning for Face Labeling CVPR 2015
Backpropagation for Energy-Efficient Neuromorphic Computing NIPS 2015
Simple, Efficient, and Neural Algorithms for Sparse Coding COLT 2015