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Changelog for v0.3.3 (#622)
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Summary: Pull Request resolved: #622

Reviewed By: eytan

Differential Revision: D25390481

Pulled By: Balandat

fbshipit-source-id: adb1b1f7e2992f078f22393ab25a8d686d5e2980
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The release log for BoTorch.


## [0.3.3] - Dec 8, 2020

Contextual Bayesian Optimization, Input Warping, TuRBO, sampling from polytopes.

#### Compatibility
* Require PyTorch >=1.7 (#614).
* Require GPyTorch >=1.3 (#614).

#### New Features
* Models (LCE-A, LCE-M and SAC ) for Contextual Bayesian Optimziation (#581).
* Implements core models from:
[High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization](https://proceedings.neurips.cc/paper/2020/hash/faff959d885ec0ecf70741a846c34d1d-Abstract.html).
Q. Feng, B. Letham, H. Mao, E. Bakshy. NeurIPS 2020.
* See Ax for usage of these models.
* Hit and run sampler for uniform sampling from a polytope (#592).
* Input warping:
* Core functionality (#607).
* Kumaraswamy Distribution (#606).
* Tutorial (8f34871652042219c57b799669a679aab5eed7e3).
* TuRBO-1 tutorial (#598).
* Implements the method from [Scalable Global Optimization via
Local Bayesian Optimization](https://proceedings.neurips.cc/paper/2019/file/6c990b7aca7bc7058f5e98ea909e924b-Paper.pdf).
D. Eriksson, M. Pearce, J. Gardner, R. D. Turner, M. Poloczek. NeurIPS 2019.

#### Bug fixes
* Fix bounds of `HolderTable` synthetic function (#596).
* Fix `device` issue in MOO tutorial (#621).

#### Other changes
* Add `train_inputs` option to `qMaxValueEntropy` (#593).
* Enable gpytorch settings to override BoTorch defaults for `fast_pred_var` and `debug` (#595).
* Rename `set_train_data_transform` -> `preprocess_transform` (#575).
* Modify `_expand_bounds()` shape checks to work with >2-dim bounds (#604).
* Add `batch_shape` property to models (#588).
* Modify `qMultiFidelityKnowledgeGradient.evaluate()` to work with `project`, `expand` and `cost_aware_utility` (#594).
* Add list of papers using BoTorch to website docs (#617).


## [0.3.2] - Oct 23, 2020

Maintenance Release
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