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Adeesh Kolluru

As seen in: Royal Society of Chemistry
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Articles

Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations

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By Amir Barati, Janghoon Ock, Adeesh Kolluru, Amir Barati Farimani
| arxiv.org
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Investigating the Error Imbalance of Large-Scale Machine Learning Potentials in Catalysis

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By Kareem Abdelmaqsoud, Raffaele Cheula, Muhammed Shuaibi, Adeesh Kolluru
| Royal Society of Chemistry Verified
Investigating the Error Imbalance of Large-Scale Machine Learning Potentials in Catalysis Machine learning potentials (MLPs) have greatly accelerated atomistic simulations for material dis- covery. The Open Catalyst 2020 (OC20) dataset is one of the largest datasets for training MLPs for heterogeneous catalysis. The mean absolute errors (MAE) of the MLPs on the energy target of the dataset have asymptotically approached about 0.2 eV over the past two years with increasingly sophisticated models.
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