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.