A pre-trained neural network selects adaptive kernels per sample point to enable accurate high-dimensional kernel density estimation.
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Wahkon unifies Kolmogorov superposition with RKHS regularization to produce a deep network whose penalized estimator is exactly the MAP under a hierarchical GP prior and achieves minimax-optimal rates.
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Adaptive Kernel Density Estimation with Pre-training
A pre-trained neural network selects adaptive kernels per sample point to enable accurate high-dimensional kernel density estimation.
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Wahkon: A Statistically Principled Deep RKHS Superposition Network
Wahkon unifies Kolmogorov superposition with RKHS regularization to produce a deep network whose penalized estimator is exactly the MAP under a hierarchical GP prior and achieves minimax-optimal rates.