Event Identification as a Decision Process with Non-linear Representation of Text

We propose scale-free Identifier Network(sfIN), a novel model for event identification in documents. In general, sfIN first encodes a document into multi-scale memory stacks, then extracts special events via conducting multi-scale actions, which can be considered as a special type of sequence labelling. The design of large scale actions makes it more efficient processing a long document. The whole model is trained with both supervised learning and reinforcement learning.Comment: 8 pages, 8 figure

Additional file 9: of Mov10 suppresses retroelements and regulates neuronal development and function in the developing brain

RNA-seq of N2a WT undifferentiated versus WT differentiated N2a. (XLSX 5557 kb