Release 0.5.0
New functionality
add support for multi-objective optimization with the expected hypervolume improvement acquisition function (#177) (#194) (#202) (#207) (#217) (#225) (#243)
add support for batch optimization via local penalization (#230) (#251)
allow custom acquisition function optimizers (#186)
add various toy objective functions: Gramacy & Lee (#168), Goldstein-Price (#169), VLMOP2, DTLZ (#190), Hartmann (#204), Rosenbrock, Ackley (#241), Shekel (#250)
Improvements
simplify single model/dataset use case (#252)
expose predict_y from GPFlow models (#254)
support arbitrary tensor-likes as inputs, not just lists (#234)
improve and track unit test code coverage (#222) (#236)
Build changes
simplify docs build and add it to build checks (#231) (#240)
add taskipy support for running tests (#219) (#244)