seminar | Deep Learning JP - Part 89

Learning What and Where to Draw (NIPS’16)

Dual Learning for Machine Translation

Value Iteration Networks

Image-to-Image Translation with Conditional Adversarial Networks

Continuous Deep Q-Learning with Model-based Acceleration

TREE-STRUCTURED VARIATIONAL AUTOENCODER

Learning Convolutional Neural Networks for Graphs

Hybrid Computing using a Neural Network with Dynamic External Memory

PGQ: COMBINING POLICY GRADIENT AND QLEARNING

SAMPLE EFFICIENT ACTOR-CRITIC WITH EXPERIENCE REPLAY

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