This version formalizes the inclusion of new features introduced from 0.7a1 to 0.7b2. An (incomplete) list of features include: - A redesigned active learning module (`graphdot.model.active_learning`). - The PBR graph reordering algorithm for graph kernel acceleration (`graphdot.graph.reorder.pbr`). - LOOCV predictions using the low-rank approximate GPR. - Significant improvement to the robustness of the training methods of GPR and Low-rank GPR models. - Allow kernel/microkernel hyperparameters to be declared as 'fixed' via the `*_bounds` arguments. - Added a `DotProduct` microkernel for vector-valued node and edge features. - Added a `.normalized` attribute to all elementary and composite microkernels. - Graph representation string can now be directly deserialized using `eval`. - New atomic adjacency options such as alternative bell-shaped compact adjacency functions (`compactbell[a,b]`), and new length scale choices using covalent radiu etc. - Perform value range check for the node and edge kernels during graph kernel creation. - Added a `to_networkx()` method to `graphdot.Graph`. - Enhanced the readability of the string representations of kernel hyperparameters using an indented print layout. - Various performance and bug fixes.