Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Improved Training with Curriculum GANs
Improved Techniques for Training GANs
Flow-GAN: Bridging implicit and prescribed learning in generative models
Towards Principled Methods for Training Generative Adversarial Networks
On Convergence and Stability of GANs
On GANs and GMMs
The Numerics of GANs
Composition and decomposition of GANs
Improving GANs Using Optimal Transport
Improved Training of Generative Adversarial Networks Using Representative Features
Automated Curriculum Learning for Neural Networks
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Improving GAN Training via Binarized Representation Entropy (BRE) Regularization
Stabilizing GAN Training with Multiple Random Projections
Good Semi-supervised Learning that Requires a Bad GAN
Generalization and equilibrium in generative adversarial nets (GANs) (invited talk)
Gradient descent GAN optimization is locally stable
KGAN: How to Break The Minimax Game in GAN
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
Analyzing the Training Processes of Deep Generative Models
Visual perception of biological motion and a model for its analysis
Paralinguistics in speech and language-State-of-the-art and the challenge
Grammar as a Foreign Language
How To Grade a Test Without Knowing the Answers --- A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing
Face Recognition using Template Matching