Codesota · Models · TimesNetTHUML5 results · 2 benchmarks
Model card

TimesNet.

THUMLopen-sourceCNN (2D temporal modeling)

Transforms 1D time series into 2D space to exploit 2D CNNs for temporal variation modeling.

§ 01 · Benchmarks

Every benchmark TimesNet has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01WeatherTime Series · Time Series Forecastingmae0.3%#3/62024-05-07source ↗
02WeatherTime Series · Time Series Forecastingmse0.3%#3/62024-05-07source ↗
03M4 CompetitionTime Series · Time Series Forecastingmase1.6%#9/132022-10-05source ↗
04M4 CompetitionTime Series · Time Series Forecastingowa0.9%#10/132022-10-05source ↗
05M4 CompetitionTime Series · Time Series Forecastingsmapi11.8%#10/132022-10-05source ↗
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.
§ 02 · Strengths by area

Where TimesNet actually performs.

Time Series
2
benchmarks
avg rank #7.0
§ 03 · Papers

2 papers with results for TimesNet.

  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. 2022-10-05· Time Series· 3 results

    TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

    Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou et al.
§ 04 · Related models

Other THUML models scored on Codesota.

Autoformer
Unknown params · 0 results
DLinear
0 results
FEDformer
Unknown params · 0 results
iTransformer
0 results
§ 05 · 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 2022-10-05, latest 2024-05-07.