Transfer learning using attentions across atomic systems with graph neural networks (TAAG)

Published in The Journal of Chemical Physics, 2022

Citation: Adeesh Kolluru, Nima Shoghi, Muhammed Shuaibi, Siddharth Goyal, Abhishek Das, C Zitnick, Zachary Ulissi, The Journal of Chemical Physics, 2022.

Introduces TAAG, a novel attention-based transfer learning approach for Graph Neural Networks which significantly improves performance for out-of-domain datasets and speeds up model training, demonstrating the potential for generalizing important aspects across different atomic system domains.

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