The performance of NewtonNet model compared with DeepMD on 13 315 randomly sampled in-distribution (ID) hold-out test configurations and 13 315 out-of-distribution (OOD) test configurations provided by the authors on the methane combustion dataset. Errors are reported in terms of mean absolute error (MAE) for energies (kcal per mol per atom) and forces (kcal mol⁻¹ Å⁻¹). We systematically reduce the amount of training data by two orders of magnitude using NewtonNet and compare it to the 578 731 data points used in the original paper by Zeng and co-workers²⁸.

Training set size	DeepMD	NewtonNet	NewtonNet	NewtonNet
	578 731	578 731	57 873	5787
Energies (ID)	0.945a	0.353	0.391	0.484
Forces (ID)	—	1.12	1.88	2.78
Energies (OOD)	3.227	3.170	3.135	3.273
Forces (OOD)	2.77	2.75	2.93	3.76

^aThe MAE on the training set reported in ref. 14 was taken as the in-distribution prediction error here.