PDEBench fluid evolution

Neural surrogates that roll out PDE solutions with less error (placeholder)

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curator Declare the evaluation and the baseline 62ab10e · 2个月前历史

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1	{
2	"domain": "engineering-energy",
3	"image": "python:3.12-slim",
4	"data": "The PDEBench and The Well training splits; the test trajectories are scored on the runner.",
5	"benchmark": {
6	"task": "PDE surrogate modelling",
7	"metric": {
8	"name": "nRMSE",
9	"better": "lower"
10	},
11	"cost": "GPU-hours",
12	"subtasks": "systems",
13	"guardrails": [
14	"Autoregressive rollout from the first ten steps, with no ground truth after them",
15	"One model per system, trained on its training split only",
16	"At most 48 GPU-hours per system"
17	],
18	"aggregate": "mean",
19	"baseline": {
20	"name": "FNO",
21	"score": 0.091,
22	"cost": 9.5,
23	"subtasks": {
24	"1D advection": 0.1281,
25	"1D Burgers": 0.1477,
26	"1D diffusion–reaction": 0.09651,
27	"2D Darcy flow": 0.05843,
28	"2D shallow water": 0.1251,
29	"2D reaction–diffusion": 0.01769,
30	"2D compressible NS": 0.1182,
31	"3D compressible NS": 0.03628
32	}
33	}
34	}
35	}