Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Deep Pyramidal Residual Networks
FractalNet: Ultra-Deep Neural Networks without Residuals
Forward Stability of ResNet and Its Variants
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex
Greedy Layer-Wise Training of Deep Networks
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train
Avoiding pathologies in very deep networks
Learning the Structure of Deep Convolutional Networks
Gradual DropIn of Layers to Train Very Deep Neural Networks
Training Deeper Convolutional Networks with Deep Supervision
DropNeuron: Simplifying the Structure of Deep Neural Networks
Refining Architectures of Deep Convolutional Neural Networks
Residual Recurrent Highway Networks for Learning Deep Sequence Prediction Models
DN-ResNet: Efficient Deep Residual Network for Image Denoising
DeepArchitect: Automatically Designing and Training Deep Architectures
Functional Gradient Boosting based on Residual Network Perception
Channel Pruning for Accelerating Very Deep Neural Networks
Spatially Adaptive Computation Time for Residual Networks
Shallow Learning For Deep Networks
Multiresolution Deep Belief Networks
A Pyramidal Neural Network For Visual Pattern Recognition
BigSR: an empirical study of real-time expressive RDF stream reasoning on modern Big Data platforms
Semantic Representation and Recognition of Continued and Recursive Human Activities
Distributionally robust chance constraints for non-linear uncertainties
Runtime-behavior based malware classification using online machine learning
Learning multiple layers of features from tiny images