Release 0.11.3

This point release fixes support for GPflux 0.2.7, which was broken when adding support for GPflux 0.3.0 in the last release.

Full Changelog: v0.11.2...v0.11.3

Release 0.11.2

This point release fixes another bug affecting the copying and saving of deep ensemble models, and also adds support for saving deep GP models.

New features
Copying and saving deep GP models (#569)

Fixes
Fix copying deep ensemble model with no optimizer callbacks (#569)

Build changes
Test against gpflux 0.3.0 and tensorflow 2.8.0 (#571)

Full Changelog: v0.11.1...v0.11.2

Release 0.11.1

This point release fixes a bug affecting the copying and saving of deep ensemble models.

Fixes
Fix copying of deep ensemble models (#567)

Full Changelog: v0.11.0...v0.11.1

Release 0.11.0

New features
SparseGaussianProcessRegression model wrapper (#531)
MonteCarloExpectedImprovement acquisition function (#393, #554)
DecoupledTrajectorySampler (#504, #556, #559)
DeepGaussianProcessDecoupledTrajectorySampler (#393, #549)
Fixed reference points for multi-objective optimization (#385)
Inducing point selectors (#511, #564)
HIPPO: HIghly Parallelizable Pareto Optimization (#519)
Saving optimization history to disk (#535)
Copying and saving deep ensemble models (#540)
MakePositive acquisition function transformation (#516)
try_get_optimal_point result helper method (#517)

Improvements
TensorBoard monitoring overhaul (#514, #515, #536, #544, #551)
Use gpflow posterior objects to speed up acquisition (#523, #532)
DeepEnsembleTrajectorySampler improvements (#541)
Avoid recompiling training loss closures (#553)
Default to compiled model optimizer for gpflow (#528)
Multiplication of mixed search spaces (#518)
Seed argument in search space sample method (#561)
Support ask-tell with uncopyable models (#545)
Make gpflux builders consistent with gpflow builders (#478)
Type checking improvements (#506, #507, #513, #521)

Build changes
Update to gpflow 2.5.2 (#522, #550, #555)
Name integration tests (#508)
Make fake8 ignore build directory (#557)
Thompson Sampling notebook (#527)
Documentation fixes (#502, #525, #542)

Full Changelog: v0.10.0...v0.11.0

Release 0.10.0

New functionality
BALD active learning acquisition function (#417)
Continuous Thompson Sampling acquisition functions (#475, #480, #486, #500)
Random Sampling acquisition function (#493)
Support for Keras models and trajectory samplers (#459, #467, #468)
Utilities for quickly constructing GPFlow models (#465, #483)

Improvements
Support for SVGP and VGP models with GIBBON (#491)
Support for covariance_between_points with multi-output GPR/SVGP/VGP models (#492)
Support splitting up acquisition function calls to reduce memory usage (#497)
Improve tensorboard logging to handle gpflux models, ask-tell optimization and wallclock timings (#469, #470, #488)
Improve static type checking for rules and samplers that depend on specific types of models (#463, #466, #474, #479, #482, #499, #501)

Build Changes
OpenAI Gym Lunar Lander tutorial (#456)
Support and test with both TF 2.4 and TF 2.5 (#484, #490)
Simplify optimizer code (#496)

Full Changelog: v0.9.1...v0.10.0

Release 0.9.1

This point release temporarily reverts the GPFlux RFF fix (#420) so as to maintain support for Tensorflow 2.4. It also adds the following functionality.

New functionality
Support for vectorized acquisition functions (#458)

Improvements
Fix TF compilation issue for VGP models (#418)

Full Changelog: v0.9.0...v0.9.1

Release 0.9.0

New functionality
t-IMSE acquisition functions (#426, #429)
Kriging Believer acquisition functions (#426, #428, #451)
Initial support for Keras (#451, #452)

Improvements
Refactor model-sampler interactions (#398)
Parallel acquisition function optimizers (#438)
Fix GPflux RandomFourierFeatures import (#420)
Use default optimizers with configs (#434)
Make AcquisitionFunctionBuilder generic on ProbabilisticModel (#433)

Build Changes
Notebook formatting (#432)
Fix test random number seeding (#450)
Active learning integration tests (#441)

Breaking Changes
ModelStack renamed to TrainableModelStack
LocalPenalizationAcquisitionFunction renamed to LocalPenalization
trieste.acquisition.function.local_penalisation renamed to greedy_batch

Full Changelog: v0.8.0...v0.9.0

Release 0.8.0

New functionality

Support for deep Gaussian processes with GPflux (#357, #364, #377)
Support for asynchronous Bayesian Optimization (#366, #374, #380, #381, #384, #386)
Active learning: predictive variance (#294) and expected feasibility (#421) acquisition functions
Tagged product search spaces (#367, #387, #403, #422)
Tensorboard monitoring support (#370, #407)
Trid (#378) and simpe quadratic (#404) objective functions

Improvements

Make datasets an optional keyword argument for rule acquisition and acquisition function preparation (#383)
Split up function.py (interfaces must now be imported from trieste.acquisition or trieste.acquisition.interfaces) (#408)
Improve config handing (support dictionary configs again; replace create_optimizer by ModelRegistry; add tutorial) (#389)
Allow empty observation for non-dominated space partitions (#356)
Allow specification of scipy optimizer kwargs for optimizing acqusition functions (#410)
Refactor model optimizers (TFOptimizer renamed to BatchOptimizer) (#372, #405)

Build changes

Speed up CI tests (#377, #390, #391, #395, #399, #404, #409)
Improved documentation (#382, #400 and various above)

Full Changelog: v0.7.0...v0.8.0

Release 0.7.0

New functionality

Ask Tell API (#346)
GPFlux interface (but no models yet) (#355)
Michalewicz function (#350)

Improvements

Support in-place updates to acquisition functions to avoid having to retrace every acquisition loop. Update existing acquisition function builders to use this. (#271, #327, #340, #349, #352)
Fix SVGP interface to be consistent with other GPflow interfaces (#320)
Refactor Pareto code. Note that hypervolume acquisition function builders are now passed partition bounds. (#328)
Simplify trust region handling (#306)

Build changes

Split model interfaces into directories (#272)
Rename trieste.type module to trieste.types (#323)
Remove homespun deepcopy functionality (#339)
Improve type checking (#307, #331, #333)
Use extend-exclude for flake8 and black (#348)
Reduce RAM usage in integration tests (#330)

Release 0.6.1

This point release updates trieste.space.Box to support empty boxes. It adds no new features.