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Deep Learning

1,856 papers

Papers per year

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Papers

Residual Networks Behave Like Ensembles of Relatively Shallow Networks NIPS 2016
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences NIPS 2016
Swapout: Learning an ensemble of deep architectures NIPS 2016
Deep Gate Recurrent Neural Network ACML 2016
Collaborative Recurrent Neural Networks for Dynamic Recommender Systems ACML 2016
Echo State Hoeffding Tree Learning ACML 2016
Deceptive Opinion Spam Detection Using Neural Network COLING 2016
Syntactic realization with data-driven neural tree grammars COLING 2016
Detecting Sentence Boundaries in Sanskrit Texts COLING 2016
Recurrent Dropout without Memory Loss COLING 2016
Consensus Attention-based Neural Networks for Chinese Reading Comprehension COLING 2016
Multi-level Gated Recurrent Neural Network for dialog act classification COLING 2016
Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network COLING 2016
Hashtag Recommendation with Topical Attention-Based LSTM COLING 2016
Object Contour Detection With a Fully Convolutional Encoder-Decoder Network CVPR 2016
Learning Relaxed Deep Supervision for Better Edge Detection CVPR 2016
Occlusion Boundary Detection via Deep Exploration of Context CVPR 2016
D3: Deep Dual-Domain Based Fast Restoration of JPEG-Compressed Images CVPR 2016
Joint Training of Cascaded CNN for Face Detection CVPR 2016
Bottom-Up and Top-Down Reasoning With Hierarchical Rectified Gaussians CVPR 2016
End-To-End Saliency Mapping via Probability Distribution Prediction CVPR 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning ICML 2016
Training Deep Neural Networks via Direct Loss Minimization ICML 2016
A Theory of Generative ConvNet ICML 2016
Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016