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Neural conditional random fields


We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Markov networks, yielding a powerful and scalable probabilistic model that we apply to signal labeling tasks.
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hal-01291978 , version 1 (22-03-2016)


  • HAL Id : hal-01291978 , version 1


Trinh Minh Tri Do, Thierry Artières. Neural conditional random fields. International Conference on Artificial Intelligence and Statistics (AISTAT), May 2010, Sardinia, Italy. pp.177-184. ⟨hal-01291978⟩
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