Team update
PixelCNN++: Improving the PixelCNN with discretized logistic mixture likelihood and other modifications
Faulty reward functions in the wild
Universe
OpenAI and Microsoft
#Exploration: A study of count-based exploration for deep reinforcement learning
On the quantitative analysis of decoder-based generative models
A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
RL²: Fast reinforcement learning via slow reinforcement learning
Variational lossy autoencoder
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Team update
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Faulty reward functions in the wild
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Universe
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OpenAI and Microsoft
9 years ago
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Variational lossy autoencoder
9 years ago
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Extensions and limitations of the neural GPU
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Report from the self-organizing conference
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Infrastructure for deep learning
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Machine Learning Unconference
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Special projects
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Concrete AI safety problems
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