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Version 0.3.0: Multi-Objective Bayesian Optimization (#472)
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Summary:
Pull Request resolved: #472

see title

Reviewed By: Balandat

Differential Revision: D22393843

fbshipit-source-id: 22f071c3e6eaaca3a09dd5db4e23f8b54450000d
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sdaulton authored and facebook-github-bot committed Jul 6, 2020
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32 changes: 32 additions & 0 deletions CHANGELOG.md
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The release log for BoTorch.


## [0.3.0] - July 6, 2020

Multi-Objective Bayesian Optimization

#### New Features
* Multi-Objective Acquisition Functions (#466)
* q-Expected Hypervolume Improvement
* q-ParEGO
* Analytic Expected Hypervolume Improvement with auto-differentiation
* Multi-Objective Utilities (#466)
* Pareto Computation
* Hypervolume Calculation
* Box Decomposition algorithm
* Multi-Objective Test Functions (#466)
* Suite of synthetic test functions for multi-objective, constrained
optimzation
* Multi-Objective Tutorial (#468)
* Abstract ConstrainedBaseTestProblem (#454)
* Add optimize_acqf_list method for sequentially, greedily optimizing 1 candidate
from each provided acquisition function (d10aec911b241b208c59c192beb9e4d572a092cd)


#### Bug fixes
* Fixed re-arranging mean in MultiTask MO models (#450).

#### Other changes
* Move gpt_posterior_settings into models.utils (#449)
* Allow specifications of batch dims to collapse in samplers (#457)
* Remove outcome transform before model-fitting for sequential model fitting
in MO models (#458)


## [0.2.5] - May 14, 2020

Bugfix Release
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2 changes: 1 addition & 1 deletion botorch/__init__.py
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from botorch.utils import manual_seed


__version__ = "0.2.5"
__version__ = "0.3.0"


__all__ = [
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2 changes: 1 addition & 1 deletion setup.py
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long_description=long_description,
long_description_content_type="text/markdown",
python_requires=">=3.7",
install_requires=["torch>=1.4", "gpytorch>=1.1.1", "scipy"],
install_requires=["torch>=1.5", "gpytorch>=1.1.1", "scipy"],
packages=find_packages(),
extras_require={
"dev": DEV_REQUIRES,
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