Temperature Forecasting on set 2023 (test) benchmark leaderboard · SOTA2 Research

Temperature Forecasting on set 2023 (test)

0.7709Error (1h)Multi-modal Transformer

Evaluation Results

Method	Links
Multi-modal Transformer2024.10		0.7709	0.9916	1.2261	1.3163	1.3852	1.3612	1.3775	1.441	1.4685	1.2598
Multi-modal Transformer2024.10		0.785	1.1293	1.4047	1.5725	1.5897	1.5775	1.6328	1.6226	1.6761	1.4434
Multi-modal Transformer2024.10		0.789	1.1146	1.4106	1.6805	1.77	1.8012	2.4541	3.3228	4.1414	2.0538
Multi-modal Transformer2024.10		0.8453	1.3104	1.9738	2.6415	2.9751	3.3225	3.6866	4.3659	4.5679	2.8543
MLP2024.10		0.8586	1.3821	2.1692	3.0583	3.4384	3.7497	3.9832	4.683	4.835	3.1286
Persistence2024.10		1.1285	2.0531	3.596	5.6626	6.4681	5.6292	4.3057	7.3789	5.3896	4.6235
MLP2024.10		1.5194	1.9444	2.054	2.4136	2.6902	2.0723	2.1444	2.0465	2.3971	2.1424
MLP2024.10		1.5682	2.2566	2.1774	2.8183	2.7663	2.9323	3.0804	3.5388	4.2048	2.8159
GNN2024.10		1.6763	2.0039	2.4243	2.8027	3.3179	3.3818	3.9041	4.4925	5.0684	3.2302
Interpolation2024.10		1.6824	1.6824	1.6824	1.6824	1.6824	1.6824	1.6824	1.6824	1.6824	1.6824
MLP2024.10		1.6848	1.7721	2.1847	2.6728	2.6778	2.5402	2.5701	2.519	2.2849	2.3229
GNN2024.10		1.7077	1.9705	2.0594	2.4264	2.7071	2.6259	3.0305	2.8871	2.429	2.4271
GNN2024.10		1.7567	2.091	2.2112	2.7139	2.8009	2.3816	2.5855	2.8181	2.2044	2.3959
Interpolation2024.10		1.7706	1.8379	1.9356	2.0467	2.1033	2.1501	—	—	—	1.974
GNN2024.10		1.7773	1.8839	2.8742	2.5763	2.8597	2.7491	3.0851	3.6259	4.1813	2.8459
Interpolation2024.10		2.0285	2.0285	2.0285	2.0285	2.0285	2.0285	2.0285	2.0285	2.0285	2.0285