Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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Dynamic Local Regret for Non-convex Online Forecasting
Sergul Aydore, Tianhao Zhu, Dean P. Foster
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A General Method for Amortizing Variational Filtering
Joseph Marino, Milan Cvitkovic, Yisong Yue
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Leveraging the Exact Likelihood of Deep Latent Variable Models
Pierre-Alexandre Mattei, Jes Frellsen
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