A transformer autoencoder with local attention learns discriminative latent features from sparse irregular time series, yielding more consistent risk estimates for electricity theft than standard methods.
https://deddie.gr/en/ kentro-enhmerwsis/deltia-tupou/deltia-typou-2023/fevrouarios-2023/ megali-simmetohi-hedno-datathon-deddie/
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Transformer autoencoder with local attention for sparse and irregular time series with application on risk estimation
A transformer autoencoder with local attention learns discriminative latent features from sparse irregular time series, yielding more consistent risk estimates for electricity theft than standard methods.