# Probabilistic Forecasting on Lorenz dataset (test)

Source: [Probabilistic Forecasting on Lorenz dataset (test)](<https://www.sota2.com/research/sota/probabilistic-forecasting-on-lorenz-dataset-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:59:52.151Z

Evaluation of probabilistic forecasting models applied to the Lorenz dataset, using the test split. Metrics include RMSE, MAE, MAPE, and KLD.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Probabilistic Forecasting |
| Dataset (including any stated split) | Lorenz dataset (test) |
| Metric | RMSE |
| Unit | SCALAR |
| Direction | Lower is better |
| Results loaded | 2 of 2 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [RMSE](<https://www.sota2.com/research/sota/probabilistic-forecasting-on-lorenz-dataset-test.md?metric=RMSE>): Lower is better; unit: SCALAR.

- [MAE](<https://www.sota2.com/research/sota/probabilistic-forecasting-on-lorenz-dataset-test.md?metric=MAE>): Lower is better; unit: SCALAR.

- [MAPE](<https://www.sota2.com/research/sota/probabilistic-forecasting-on-lorenz-dataset-test.md?metric=MAPE>): Lower is better; unit: SCALAR.

- [KLD](<https://www.sota2.com/research/sota/probabilistic-forecasting-on-lorenz-dataset-test.md?metric=KLD>): Lower is better; unit: SCALAR.

## Recorded results

| Method | RMSE | Result date | Report paper |
| --- | --- | --- | --- |
| G-regression | 2.91 | Not recorded | 68fa65f91e209131cea0d9aa |
| ForGAN | 4.06 | Not recorded | 68fa65f91e209131cea0d9aa |

### G-regression

RMSE: 2.91. Result ID: 698cd48b8b517eb4331d0816.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65f91e209131cea0d9aa.md>)

Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction.

### ForGAN

RMSE: 4.06. Result ID: 698cd48b8b517eb4331d0817.

[Reporting paper](<https://www.sota2.com/research/paper/68fa65f91e209131cea0d9aa.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa65f91e209131cea0d9aa.md>)

[Implementation](<https://cloud.dfki.de/owncloud/index.php/s/KGJm5iNKrCnAwEg>)

Recorded evaluation configuration: {"Cell Type (T)":"GRU","Generator Cells (RG)":8,"Discriminator Cells (RD)":64,"Noise Vector (N)":32,"Look-back window (C)":24,"Discriminator Iterations (Diter)":2}. This record does not assert independent reproduction.

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