K-Splanifolds
A regression method based on a fast K-dimensional Hermite spline manifold algorithm, using spline blocks to construct piecewise-smooth manifolds, intended to provide an efficient alternative for general regression problems.
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An independent researcher recently posted a demo video on Reddit comparing the performance of his proposed K-Splanifolds version 3 (KS3) against a multi-layer perceptron (MLP) in fitting a 4D Mandelbulb fractal.
K-Splanifolds is a regression method based on a fast K-dimensional Hermite spline manifold algorithm.
KS3 is the third version of the K-Splanifolds algorithm, with core improvements in convergence efficiency and hardware adaptability.
KS uses spline blocks to construct a piecewise-smooth manifold, thereby reducing the number of iterations needed for training while maintaining expressiveness.
The author has released the code for all three versions and the KS1 paper on GitHub.
KS is not designed to replace deep learning but to provide a more efficient alternative for regression problems.
In K-Splanifolds, the algorithm partitions the input space into multiple K-dimensional blocks, constructs a local manifold within each block using Hermite splines, and then forms a global function through smooth stitching; each sample activates only a few blocks, reducing redundant computation in backpropagation.
All Facts (7)
KS uses spline blocks to construct a piecewise-smooth manifold, thereby reducing the number of iterations needed for training while maintaining expressiveness.
50%UnverifiedK-Splanifolds is a regression method based on a fast K-dimensional Hermite spline manifold algorithm.
50%UnverifiedKS3 is the third version of the K-Splanifolds algorithm, with core improvements in convergence efficiency and hardware adaptability.
50%UnverifiedIn K-Splanifolds, the algorithm partitions the input space into multiple K-dimensional blocks, constructs a local manifold within each block using Hermite splines, and then forms a global function through smooth stitching; each sample activates only a few blocks, reducing redundant computation in backpropagation.
50%UnverifiedThe author has released the code for all three versions and the KS1 paper on GitHub.
50%UnverifiedKS is not designed to replace deep learning but to provide a more efficient alternative for regression problems.
50%UnverifiedAn independent researcher recently posted a demo video on Reddit comparing the performance of his proposed K-Splanifolds version 3 (KS3) against a multi-layer perceptron (MLP) in fitting a 4D Mandelbulb fractal.
50%