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A convolution-inspired network beats transformers at classifying cuneiform tablet metadata from 3D point clouds, despite limited labeled data.
Achieve Gaussian Process-level confidence bounds in binary classification with a fraction of the computational cost using Wilson Score Kernel Density Estimation.
