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arXiv Machine Learning By Yuzhi Liu, Duo Zhang, Anyang Peng, Weinan E, Linfeng Zhang, Han Wang

Mixture of experts architectures for machine learning interatomic potentials

Read the original on arXiv Machine Learning →

arXiv:2603. 07977v3 Announce Type: replace-cross Abstract: Machine Learning Interatomic Potentials (MLIPs) enable accurate large-scale atomistic simulations, yet improving their expressive capacity efficiently remains challenging.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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