Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: Evolving deep unsupervised convolutional networks for vision-based reinforcement learning
Evolving large-scale neural networks for vision-based reinforcement learning
Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Deep auto-encoder neural networks in reinforcement learning
Early Visual Concept Learning with Unsupervised Deep Learning
Recent Progress in Deep Reinforcement Learning for Computer Vision and NLP
Training Deeper Convolutional Networks with Deep Supervision
Deep Nets: What have they ever done for Vision?
Exploring convolutional networks for end-to-end visual servoing
scalable deep reinforcement learning for vision - based robotic manipulation .
WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks
Multi-focus Attention Network for Efficient Deep Reinforcement Learning
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Iterative Visual Reasoning Beyond Convolutions
Visual Navigation with Actor-Critic Deep Reinforcement Learning
Task-Driven Convolutional Recurrent Models of the Visual System
Unsupervised Meta-Learning for Reinforcement Learning
Visual Attention Guided Deep Imitation Learning
Visual Servoing from Deep Neural Networks
Evolution-Guided Policy Gradient in Reinforcement Learning
UberNet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited Memory
Webs of five-branes and N=2 superconformal field theories
perspective - tacit knowledge and knowledge conversion : controversy and advancement in organizational knowledge creation theory .
Beyond the Transfer-and-Merge Wordnet Construction: plWordNet and a Comparison with WordNet
Motivational Incongruence and Well-Being at the Workplace: Person-Job Fit, Job Burnout, and Physical Symptoms
Generalization in Reinforcement Learning: Successful Examples Using Sparse Coarse Coding