KAE, an autoencoder with polynomial KAN layers, achieves lower reconstruction error and better downstream task performance than standard autoencoders and other KAN variants on four image benchmarks.
Self pre- training with masked autoencoders for medical image classification and segmentation
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KAE: Kolmogorov-Arnold Auto-Encoder for Representation Learning
KAE, an autoencoder with polynomial KAN layers, achieves lower reconstruction error and better downstream task performance than standard autoencoders and other KAN variants on four image benchmarks.