seminar | Deep Learning JP - Part 86

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Variational Dropout Sparsifies Deep Neural Networks

Diet Networks: Thin Parameters for Fat Genomics

Semi-Supervised QA with Generative Domain-Adaptive Nets

Unsupervised Cross-Domain Image Generation

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

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