Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Abstraction hierarchy in deep learning neural networks
Deep Learning in Neural Networks: An Overview
Generalization in Deep Networks: The Role of Distance from Initialization
design and evolution of modular neural network architectures .
The Power of Depth for Feedforward Neural Networks
Understanding Representations Learned in Deep Architectures
Distilling the Knowledge in a Neural Network
Shallow Learning For Deep Networks
A geometric perspective on the robustness of deep networks
Layer-Wise Relevance Propagation for Deep Neural Network Architectures
Understanding symmetries in deep networks
An Overview of Convolutional Neural Network Architectures for Deep Learning
Global Explanations of Neural Networks: Mapping the Landscape of Predictions
Representation Benefits of Deep Feedforward Networks
The loss surface of deep and wide neural networks
Understanding Deep Neural Networks with Rectified Linear Units
A Framework for Designing the Architectures of Deep Convolutional Neural Networks
Understanding deep learning requires rethinking generalization
Stronger generalization bounds for deep nets via a compression approach
Deep Complex Networks
Comparison of Training Methods for Deep Neural Networks
Seasonal influenza vaccine policy, use and effectiveness in the tropics and subtropics – a systematic literature review
On the quantitative analysis of deep belief networks
The total artificial heart for biventricular heart failure and beyond.
Role-Dynamics: Fast Mining of Large Dynamic Networks
Event Representations for Automated Story Generation with Deep Neural Nets