seminar | Deep Learning JP - Part 81

Energy-based generative adversarial networks

Opening the Black Box of Deep Neural Networks via Information

Improved Training of Wasserstein GANs

Parallel Multiscale Autoregressive Density Estimation

Training RNNs as Fast as CNNs

The Conditional Analogy GAN: Swapping Fashion Articles on People Images

Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses

MoCoGAN: Decomposing Motion and Content for Video Generation

DeepNav: Learning to Navigate Large Cities

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

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