Codesota · Models · DLinearTHUML5 results · 2 benchmarks
Model card

DLinear.

THUMLopen-sourceLinear

Decomposes series into trend+seasonal components and applies a linear layer on each.

§ 02 · Benchmarks

Every benchmark DLinear has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01WeatherTime-series · Time-series forecastingmae0.3%#1/62024-05-07source ↗
02M4 CompetitionTime-series · Time-series forecastingmase2.1%#1/132022-05-26source ↗
03M4 CompetitionTime-series · Time-series forecastingowa1.1%#1/132022-05-26source ↗
04WeatherTime-series · Time-series forecastingmse0.3%#2/62024-05-07source ↗
05M4 CompetitionTime-series · Time-series forecastingsmapi13.6%#2/132022-05-26source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area

Where DLinear actually performs.

Time-series
2
benchmarks
avg rank #1.4
§ 04 · Papers

2 papers with results for DLinear.

  1. 2024-05-07· Time Series· 2 results

    iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

    Yong Liu, Tengge Hu, Haoran Zhang, Ling Jin et al.
  2. 2022-05-26· Time Series· 3 results

    Are Transformers Effective for Time Series Forecasting?

    Ailing Zeng, Muxi Chen, Lei Zhang, Qiang Xu
§ 05 · Related models

Other THUML models scored on Codesota.

Autoformer
Unknown params · 0 results
FEDformer
Unknown params · 0 results
TimesNet
0 results
iTransformer
0 results
§ 06 · Sources & freshness

Where these numbers come from.

TimeMixer++ Table 2
3
results
iTransformer Table 1
2
results
5 of 5 rows marked verified. · first result 2022-05-26, latest 2024-05-07.