papers | Deep Learning JP - Part 83

Bridging the Gap Between Value and Policy Based Reinforcement Learning

StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks

Generative Adversarial Imitation Learning

QUASI-RECURRENT NEURAL NETWORKS

Wasserstein GAN

Towards Principled Methods for Training Generative Adversarial Networks

Exploiting Cyclic Symmetry in Convolutional Neural Networks

Understanding deep learning requires rethinking generalization

Stochastic Neural Networks for Hierarchical Reinforcement Learning

Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning

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