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Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training Yefan Zhou
Neural Information Processing Systems
However, such a global learning rate schedule does not take into account the structural characteristics of neural networks (NNs).
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It is common that these data themselves have inherently complicated 3D geometric structures.
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Equivariant Neural Operator Learning with Graphon Convolution
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It is common that these data themselves have inherently complicated 3D geometric structures.
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9c26a48b7ebd37bc3e979c8651fc3649-Paper-Conference.pdf
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Exploiting symmetry inherent in data can significantly improve the sample efficiency of alearning procedure and the generalization of learned models.
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