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Found 2 papers, 1 papers with code
Multitask methods for predicting molecular properties from heterogeneous data
Data generation remains a bottleneck in training surrogate models to predict molecular properties.
Rotation Equivariant Operators for Machine Learning on Scalar and Vector Fields
We develop theory and software for rotation equivariant operators on scalar and vector fields, with diverse applications in simulation, optimization and machine learning.
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