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Found 2 papers, 1 papers with code
Robust Adversarial Defense by Tensor Factorization
This study underscores the potential of integrating tensorization and low-rank decomposition as a robust defense against adversarial attacks in machine learning.
Less is more: sampling chemical space with active learning
In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials.
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