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Terminology-based Text Embedding for Computing Document Similarities on Technical Content
We propose in this paper a new, hybrid document embedding approach in order to address the problem of document similarities with respect to the technical content.
Position-based Content Attention for Time Series Forecasting with Sequence-to-sequence RNNs
We propose here an extended attention model for sequence-to-sequence recurrent neural networks (RNNs) designed to capture (pseudo-)periods in time series.
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