Maintenance Release, Optimizer Improvements

New Features

• NP Regression Model w/ LIG Acquisition (#2683).
• Fully Bayesian Matern GP with dimension scaling prior (#2855).
• Option for input warping in non-linear fully Bayesian GPs (#2858).
• Support for condition_on_observations in FullyBayesianMultiTaskGP (#2871).
• Improvements to optimize_acqf_mixed_alternating:
  • Support categoricals in alternating optimization (#2866).
  • Batch mixed optimization (#2895).
  • Non-equidistant discrete dimensions for optimize_acqf_mixed_alternating (#2923).
  • Update syntax for categoricals in optimize_acqf_mixed_alternating (#2942).
  • Equality constraints for optimize_acqf_mixed_alternating (#2944).
• Multi-output acquisition functions and related utilities:
  • Multi-Output Acquisition Functions (#2935).
  • Utility for greedily selecting an approximate hypervolume maximizing subset (#2936).
  • Update optimize with NSGA-II (#2937).
  • Add utility for running pymoo NSGA-II (#2868).
• Batched L-BFGS-B for more efficient acquisition function optimization (#2870, #2892).
• Pathwise Thompson sampling for ensemble models (#2877).
• ROBOT tutorial notebook (#2883).
• Add community notebooks to the botorch.org website (#2913).

Bug Fixes

• Fix model paths in prior fitted networks (#2843).
• Fix a bug where input transforms were not applied in fully Bayesian models in train mode (#2859).
• Fix local Y vs global Y_Train in generate_batch function in TURBO tutorial (#2862).
• Fix CUDA support for FullyBayesianMTGP (#2875).
• Fix edge case with NaNs in is_non_dominated (#2925).
• Normalize for correct fidelity in qLowerBoundMaxValueEntropy (#2930).
• Bug: Botorch_community VBLLModel posterior doesn't work with single value tensor (#2929).
• Fix variance shape bug in Riemann posterior (#2939).
• Fix input constructor for LogProbabilityOfFeasibility (#2945).
• Fix AugmentedRosenbrock problem and expand testing for optimizers (#2950).

Other Changes

• Improved documentation for optimize_acqf (#2865).
• Fully Bayesian Multi-Task GP cleanup (#2869).
• average_over_ensemble_models decorator for acquisition functions (#2873).
• Changes to I-BNN tutorial (#2889).
• Allow batched fixed features in gen_candidates_scipy and gen_candidates_torch (#2893)
• Refactor of MultiTask / FullyBayesianMultiTaskGP to use ProductKernel and IndexKernel (#2908).
• Various changes to PFNs to improve Ax compatibility (#2915, #2940).
• Eliminate expensive indexing in separate_mtmvn (#2920).
• Added reset method to StoppingCriterion (#2927).
• Simplify closure dispatch (#2947).
• Add BaseTestProblem.is_minimization_problem property (#2949).
• Simplify NdarrayOptimizationClosure (#2951).