Overview of Grace Interatomic Potentials Practical Tutorial For Parameterization And Usage
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Let's Talk Research Episode 3: Machine-learned interatomic potentials (MLIPs)
[JC] Machine Learning Interatomic Potentials
Christoph Ortner - Modelling Atomic Properties with the Atomic Cluster Expansion - IPAM at UCLA
How to train your first ML Interatomic Potential using NequIP [TUTORIAL 1]
Daniel Schwalbe Koda: Machine learning for interatomic potentials
Beyond Interatomic Potentials - Further Acceleration of Atomic-Scale SImulations
Interatomic forcefield parameterization by active learning
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
Lec 43 Machine learned interatomic potentials hands on
Molecular Dynamics with Neural Equivariant Interatomic Potentials
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Last Updated: August 16, 2026
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![How to train your first ML Interatomic Potential using NequIP [TUTORIAL 1]](https://i.ytimg.com/vi/xuY5-Pf_Wxc/mqdefault.jpg)
