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Found 2 papers, 2 papers with code
Recovering individual emotional states from sparse ratings using collaborative filtering
We validate our approach across three different experimental contexts by recovering dense individual ratings using only a small subset of the original data.
Modeling emotion in complex stories: the Stanford Emotional Narratives Dataset
We begin by assessing the state-of-the-art in time-series emotion recognition, and we review contemporary time-series approaches in affective computing, including discriminative and generative models.
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