Time2Vec learns a vector representation of time that improves model performance when used in place of raw time inputs across various models and problems.
Taming the waves: sine as activation function in deep neural networks
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.LG 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
Proposes a model-agnostic diachronic entity embedding function to extend static KG embedding models for temporal knowledge graph completion, with a proof that the SimplE combination is fully expressive.
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Time2Vec: Learning a Vector Representation of Time
Time2Vec learns a vector representation of time that improves model performance when used in place of raw time inputs across various models and problems.
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Diachronic Embedding for Temporal Knowledge Graph Completion
Proposes a model-agnostic diachronic entity embedding function to extend static KG embedding models for temporal knowledge graph completion, with a proof that the SimplE combination is fully expressive.