dls-2017 | Deep Learning JP

MUTAN: Multimodal Tucker Fusion for Visual Question Answering

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks

Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

Deep Reinforcement Learning that Matters

Population Based Training of Neural Networks

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

Backpropagation through the Void: Optimizing control variates for black-box gradient estimation

Rainbow: Combining Improvements in Deep Reinforcement Learning

Controllable Invariance through Adversarial Feature Learning

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