Multivariate Time-series Forecasting on Traffic (MAE, RMSE, RSE, CORR) benchmark leaderboard · SOTA2 Research

Multivariate Time-series Forecasting on Traffic (MAE, RMSE, RSE, CORR)

0.0257MAEDA-SPS

Evaluation Results

Method	Links
DA-SPS2026.01		0.0257	0.0406	0.3775	0.9608
DA-Conv-LSTM2026.01		0.028	0.0405	0.3727	0.956
DA-SPS2026.01		0.0285	0.0448	0.4165	0.9568
TCLN2026.01		0.0287	0.0448	0.4126	0.954
LSTNet2026.01		0.029	0.0436	0.4014	0.9543
DA-SPS2026.01		0.0291	0.0435	0.4041	0.9604
TS-Conv-LSTM2026.01		0.0294	0.0463	0.4263	0.9546
DA-SPS2026.01		0.0297	0.0438	0.4066	0.9499
TCLN2026.01		0.0302	0.0441	0.4062	0.9504
DA-RNN2026.01		0.0304	0.0458	0.4219	0.9538
LSTM2026.01		0.0306	0.0464	0.4273	0.9559
TS-Conv-LSTM2026.01		0.0308	0.0482	0.4439	0.9573
LSTNet2026.01		0.0312	0.0477	0.439	0.9457
TS-Conv-LSTM2026.01		0.0313	0.0484	0.4455	0.9548
TS-Conv-LSTM2026.01		0.0314	0.0473	0.4351	0.9544
LSTNet2026.01		0.0321	0.0482	0.4434	0.9385
CNN2026.01		0.0322	0.0477	0.4395	0.9603
TCLN2026.01		0.0329	0.0493	0.454	0.9563
DA-Conv-LSTM2026.01		0.0332	0.0474	0.4365	0.9475
LSTNet2026.01		0.0342	0.0502	0.4625	0.9538
CNN2026.01		0.0346	0.0515	0.4742	0.9477
CNN2026.01		0.0349	0.0509	0.469	0.9533
DA-RNN2026.01		0.0351	0.0498	0.4584	0.9486
DA-RNN2026.01		0.0354	0.0513	0.4718	0.9546
LSTM2026.01		0.0361	0.0517	0.4762	0.9662
CNN2026.01		0.0365	0.0533	0.4906	0.9521
LSTM2026.01		0.0369	0.0535	0.4924	0.9555
DA-Conv-LSTM2026.01		0.0385	0.0547	0.504	0.9554
LSTM2026.01		0.0388	0.0569	0.5239	0.9502
DA-RNN2026.01		0.0395	0.0525	0.4832	0.9379
TCLN2026.01		0.0395	0.056	0.5156	0.9589
DA-Conv-LSTM2026.01		0.0422	0.0575	0.529	0.9481