2021-05-18 · conference-paper · Time Series Analysis and Forecasting · en
highly citedClaims drawn from cited facts, not live model generation.
This paper presents a conference contribution on the primary topic of time series analysis and forecasting, focusing on efficient transformer designs for long sequence prediction. As a conference paper, this work has undergone formal peer review, so its findings warrant more weight than an unreviewed preprint.
4 cited facts
A small team of three researchers authored this work.
1 cited fact
With 6,680 citations, this work is already an established reference point in its field, having crossed the threshold for outsized influence. It draws on 45 references.
3 cited facts
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting is a conference-paper, focusing on Time Series Analysis and Forecasting, published in 2021.
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting has 6,680 citations in our record, placing it among the highly cited works we track.
Our record lists 3 authors for Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting and references 45 other works. Author names aren't in our data yet — the source link on the page lists the full byline.
Source facts, citations, and refresh stamp for this record.
Sources: openalex_works