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bases 0.2.0

• mgcv smooth interface via s() for more flexible penalization
• New b_nn() for neural network basis expansion
• New b_tpsob() for tensor product Sobolev space basis expansion (Zhang and Simon 2023)
• New b_gff() for graph Fourier features for regression on spatial and graph-structured data. Requires RSpectra package for efficient eigendecomposition, and either adj or igraph for graph representation.
• New b_conv() for random convolutional features for regression on images
• More efficient b_ker() option for many predictions
• Control automatic leaf pruning in b_bart()
• New vignette on other packages that help produce basis expansions or embeddings.

bases 0.1.2

• Basis expansions for Gaussian processes / kernel ridge regression, random Fourier features, BART prior features, and n-way interactions
• Lightweight ridge regression routine
• Gaussian, Laplace, Rational quadratic, Matérn, and periodic kernels
• Support for recipes package

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.