Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: NONPARAMETRIC APPROACHES FOR TRAINING DEEP GENERATIVE NETWORKS
Towards Principled Methods for Training Generative Adversarial Networks
Exploring strategies for training deep neural networks
Comparative Study on Generative Adversarial Networks
Self-Supervised Generative Adversarial Networks.
Bidirectional recurrent neural networks as generative models
Improved Techniques for Training GANs
Directing Generative Networks with Weighted Maximum Mean Discrepancy
Dual Discriminator Generative Adversarial Nets
Intrinsic disentanglement: an invariance view for deep generative models
Max-Margin Deep Generative Models for (Semi-)Supervised Learning
Variational Approaches for Auto-Encoding Generative Adversarial Networks
A Powerful Generative Model Using Random Weights for the Deep Image Representation
Generalization and equilibrium in generative adversarial nets (GANs) (invited talk)
Generative Modeling of Convolutional Neural Networks
Metric Learning-based Generative Adversarial Network
Modular Generative Adversarial Networks
Flow-GAN: Bridging implicit and prescribed learning in generative models
Approximation and Convergence Properties of Generative Adversarial Learning
Language Generation with Recurrent Generative Adversarial Networks without Pre-training
Deep Structured Generative Models
learning multiple layers of representation .
Anticipatory Functions, Digital-Analog Forms and Biosemiotics: Integrating the Tools to Model Information and Normativity in Autonomous Biological Agents
Nutritional strategies to reduce heat stress in broilers and broiler breeders.
Toward Self-Growing Soft Robots Inspired by Plant Roots and Based on Additive Manufacturing Technologies
Weighted Coverage based Reviewer Assignment