The Next Input updates
Browse every published The Next Input update in a calm card overview with images, dates, and direct access to each article.
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OpenAI and Microsoft
We’re working with Microsoft to start running most of our large-scale experiments on Azure.
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#Exploration: A study of count-based exploration for deep reinforcement learning
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On the quantitative analysis of decoder-based generative models
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A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models
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RL²: Fast reinforcement learning via slow reinforcement learning
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Variational lossy autoencoder
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Extensions and limitations of the neural GPU
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Semi-supervised knowledge transfer for deep learning from private training data
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Report from the self-organizing conference
Last week we hosted over a hundred and fifty AI practitioners in our offices for our first self-organizing conference on machine learning.
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Transfer from simulation to real world through learning deep inverse dynamics model
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Infrastructure for deep learning
Deep learning is an empirical science, and the quality of a group’s infrastructure is a multiplier on progress. Fortunately, today’s open-source ecosystem makes it possible for anyone to build great deep learning infrastructure.
The Next Input update
Machine Learning Unconference
Title: Machine Learning Unconference
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