v0.18.0

Compatibility

• Replace Pyro with NumPyro for fully Bayesian NUTS inference, yielding a large
  reduction in fit time (#3247).
• Require PyTorch>=2.4 (#3311).

New Features

• OrthogonalAdditiveGP with component-wise inference (#3187).
• Add custom_fit and compute_loss protocols for fitting extensibility (#3232).
• LatentKroneckerGP with customized GPyTorch inference (#3234).
• Conditional kernel GP for hierarchical search spaces (#3284).
• Add LearnedFeatureImputation input transform and wire transfer-learning
  support for MultiTaskGP (#3281, #3285, #3286, #3296, #3299).

Bug Fixes

• Fix inconsistent output shapes when all features are fixed in optimize_acqf (#3241).
• Return TorchPosterior for non-MVN distributions in ApproximateGPyTorchModel (#3242).
• Fix continuous_step crash when fixed_features cover all dims (#3249).
• Fix silent feature misalignment in HeterogeneousMTGP.posterior() (#3254).
• Fix tensor-valued fixed_features shape mismatch in infeasible projection (#3259).
• Fix PairwiseGP stored-state management for eval and CV (#3272).
• Impute per-dim empirical mean for missing features in HeterogeneousMTGP (#3294).
• Fix numerical precision in MultivariateNormalQMCEngine eigendecomposition on
  CUDA (#3224).

Other Changes

• Use parallel L-BFGS for fitting batched multi-output models (#3207).
• Optionally return acquisition values from candidate generation (#3209).
• Clean up nits across the acquisition module (#3210).
• Replace deprecated torch.inverse/torch.det with torch.linalg
  equivalents (#3213).
• Use logsumexp for numerically stable mixture entropy in BALD (#3222).
• Support cache_root for low-rank kernels (#3223).
• Support a tensor of taus in MAP SAAS (#3225).
• Support discrete parameters, inequality constraints, and ref_point in
  optimize_with_nsgaii / MOO input constructors (#3219, #3220, #3229).
• Replace the FitGPyTorchMLL and GetLossClosure dispatchers with isinstance
  checks (#3233, #3235).
• Support pathwise Thompson sampling as an option in the acquisition function
  factory (#3237).
• Add _supports_batched_models attribute to models that don't support
  batching (#3239).
• Update fixed_features type hints and docstrings in OptimizeAcqfInputs (#3240).
• Use slice-based indexing in separate_mtmvn for the non-interleaved case (#3246).
• Support observation noise in the Log outcome transform (#3245).
• Add BetaPrior support for correlation parameters and a default
  BetaPrior(2.5, 1.5) for MultiTaskGP task covariance, with setting_closure
  on PositiveIndexKernel for prior support (#3266, #3267, #3271).
• Speed up qLogEHVI using a fused kernel (#3275).
• Project initial conditions onto the equality constraint manifold (#3278).
• Fix DeprecationWarning in Standardize.untransform_posterior (#3279).
• Add untransform support to efficient LOO cross-validation (#3288).
• Add lean BoTorch targets and make JAX/numpyro imports lazy to avoid the
  JAX/numpyro dependency (#3277, #3291, #3292, #3293).
• Update MultiTaskGP docstring (#3307).

Changes to botorch_community & community notebooks

• FuRBO tutorial (#3290).
• Add Local Entropy Search (LES) acquisition function and a community notebook
  demonstrating it on Branin (#3302).