Model Architecture

FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters CVPR 2016 FPNN: Field Probing Neural Networks for 3D Data NeurIPS 2016 Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree AISTATS 2016 Gradual DropIn of Layers to Train Very Deep Neural Networks CVPR 2016 Group Equivariant Convolutional Networks ICML 2016 Interpretation of Low Dimensional Neural Network Bottleneck Features in Terms of Human Perception and Production Interspeech 2016 Learning Relaxed Deep Supervision for Better Edge Detection CVPR 2016 Learning Sensor Multiplexing Design through Back-propagation NeurIPS 2016 Learning Structured Sparsity in Deep Neural Networks NeurIPS 2016 Learning the Number of Neurons in Deep Networks NeurIPS 2016 Modeling Time-Frequency Patterns with LSTM vs. Convolutional Architectures for LVCSR Tasks Interspeech 2016 Modulation Spectral Features for Predicting Vocal Emotion Recognition by Simulated Cochlear Implants Interspeech 2016 Multi-Attribute Factorized Hidden Layer Adaptation for DNN Acoustic Models Interspeech 2016 Multi-Bias Non-linear Activation in Deep Neural Networks ICML 2016 Multimodal Residual Learning for Visual QA NeurIPS 2016 Neural Module Networks CVPR 2016 Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep Networks ICML 2016 On the Appropriateness of Complex-Valued Neural Networks for Speech Enhancement Interspeech 2016 On the Efficient Representation and Execution of Deep Acoustic Models Interspeech 2016 Optimal Architectures in a Solvable Model of Deep Networks NeurIPS 2016 PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions NeurIPS 2016 Quantized Convolutional Neural Networks for Mobile Devices CVPR 2016 Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation CVPR 2016 Refining Architectures of Deep Convolutional Neural Networks CVPR 2016 Sparsifying Neural Network Connections for Face Recognition CVPR 2016