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Neural conditional random fields
AISTATS, (2010): 177-184
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We propose a non-linear graphical model for structured prediction. It combines the power of deep networks to extract high level features with the graphical frame- work of Markov networks, yielding a powerful and scalable model that we apply to signal labeling tasks.
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