[Diff since v0.1.6](v0.1.6...v0.1.7)

**Merged pull requests:**
- Evaluate torch model to get output dimension (#166) (@Robbybp)
- Prep for v0.1.7 (#167) (@odow)

**Closed issues:**
- Don't rely on `out_features` to get output dimension of PytorchModel (#165)

[Diff since v0.1.5](v0.1.5...v0.1.6)

**Merged pull requests:**
- [docs] clarify instructions to load PythonCall (#163) (@odow)
- Prep for v0.1.6 (#164) (@odow)

**Closed issues:**
- Failed to reproduce the PytorchModel examples (#162)

[Diff since v0.1.4](v0.1.4...v0.1.5)

**Merged pull requests:**
- Add `gray_box_device` option for PytorchModel (#159) (@Robbybp)
- Prep for v0.1.5 (#160) (@odow)
- Fix flakey tests (#161) (@odow)

[Diff since v0.1.3](v0.1.3...v0.1.4)

**Merged pull requests:**
- Add bound constraints to the Formulation object (#155) (@odow)
- [docs] improvements to the docstrings (#156) (@odow)
- [docs] fix various typos (#157) (@odow)
- Prep for v0.1.4 (#158) (@odow)

[Diff since v0.1.2](v0.1.2...v0.1.3)

**Merged pull requests:**
- Delete .github/workflows/documentation-deploy.yml (#150) (@odow)
- [docs] improve manual for NN extensions (#152) (@odow)
- Fix documentation link in README.md (#153) (@odow)
- Prep for v0.1.3 (#154) (@odow)

**Closed issues:**
- Review feedback (#82)
- Tag did not trigger documentation build (#145)
- [docs] improve manual sections (#151)

[Diff since v0.1.1](v0.1.1...v0.1.2)

**Merged pull requests:**
- Add DOCUMENTER_KEY (#148) (@odow)
- Prep for v0.1.2 (#149) (@odow)

[Diff since v0.1.0](v0.1.0...v0.1.1)

**Merged pull requests:**
- Update installation instructions for registered package (#141) (@odow)
- Create documentation-deploy.yml (#146) (@odow)
- Prep for v0.1.1 (#147) (@odow)

**Merged pull requests:**

- Add package skeleton and a basic implementation of LinearRegression (#2) (@odow)
- Add GLM package extension (#4) (@odow)
- Use Predictor instead of Model to distinguish from optimization model (#5) (@odow)
- Add support for LogisticRegression (#6) (@odow)
- Add docstrings (#7) (@odow)
- Add UnivariateNormalDistribution (#8) (@odow)
- Add preliminary NN support (#9) (@odow)
- Remove add_predictor! (#10) (@odow)
- Propagate variable bounds where possible (#11) (@odow)
- Pause actions until repo is open-sourced (#12) (@odow)
- Simplify to make extensions implement add_predictor (#13) (@odow)
- Add test for relu kwarg (#14) (@odow)
- Improve variable bound propagation in ReLU layers (#15) (@odow)
- Add Omelette.ReLU (#17) (@odow)
- Test and fix doctests (#18) (@odow)
- Add Sigmoid, SoftPlus, and Tanh layers (#19) (@odow)
- Fix test_GLM.jl (#20) (@odow)
- Support other activation functions in Lux extension (#21) (@odow)
- Tweak GLM logistic regression layer (#22) (@odow)
- Rename to MathOptAI.jl (#23) (@odow)
- Use predictor consistently instead of model (#24) (@odow)
- Add Flux.jl extension (#25) (@odow)
- Improve extension docstrings (#26) (@odow)
- Rename LinearRegression to Affine (#28) (@odow)
- Remove LogisticRegression predictor (#29) (@odow)
- Allow non-variable input vectors (#30) (@odow)
- Add matrix input/output method for add_predictor (#31) (@odow)
- Add StatsModels extension (#32) (@odow)
- Make DataFrames a weakdep (#33) (@odow)
- Fix code highlighting (#34) (@odow)
- Switch to LANL's BSD license (#36) (@odow)
- [docs] add MNIST tutorial (#37) (@odow)
- Add initial skeleton of the documentation (#38) (@odow)
- Rename added variables to moai_ (#39) (@odow)
- Add student ennrollment tutorial (#40) (@odow)
- Add SoftMax predictor (#41) (@odow)
- [docs] add manual section (#42) (@odow)
- Add kwarg option to extension methods (#46) (@odow)
- Fix Flux Float32 warning (#47) (@odow)
- [docs] add design principles (#48) (@odow)
- Remove usage of Lux.Experimental (#49) (@odow)
- Fix formatting (#50) (@odow)
- Fix various docstrings (#51) (@odow)
- Add logo (#52) (@odow)
- [docs] update mnist tutorial (#53) (@odow)
- Add BinaryDecisionTree (#54) (@odow)
- [docs] fix BinaryDecisionTree docstring (#55) (@odow)
- [docs] add docstrings for extensions (#56) (@odow)
- Standardize naming of test modules (#57) (@odow)
- Add tests for DecisionTreeExt (#58) (@odow)
- [docs] add dimension colum to predictor table (#59) (@odow)
- Add AbstractGPsExt (#60) (@odow)
- Fix test_DecisionTree for points near breakpoints (#61) (@odow)
- Remove UnivariateNormalDistribution in favor of Quantile (#62) (@odow)
- [docs] update docs with new extensions (#63) (@odow)
- Update README.md (#64) (@odow)
- Add PytorchModel and tutorial (#69) (@odow)
- Add ReducedSpace{<:AbstractPredictor} layer (#72) (@odow)
- Fix tests for update to MOI variable ordering (#73) (@odow)
- Add `reduced_space` option for PyTorchModel predictor (#76) (@Robbybp)
- Add methods for show(io::IO, ::AbstractPredictor) (#77) (@odow)
- Add build_predictor (#78) (@odow)
- Add CondaPkg to test/Project.toml (#79) (@odow)
- [breaking] return a formulation object (#80) (@odow)
- Various miscellaneous fixes (#81) (@odow)
- Relax type restrictions to support JuMP.AbstractModel (#83) (@odow)
- Allow nested ReducedSpace predictors (#84) (@odow)
- Various documentation improvements (#85) (@odow)
- [docs] add more design principles and add PyTorch manual page (#86) (@odow)
- Fix deprecation warning in tests (#88) (@odow)
- Add Scale predictor (#89) (@odow)
- [docs] remove Scaling section from design_principles.md (#91) (@odow)
- [docs] add inputs are Vectors to design principles (#93) (@odow)
- Fix typos in Scale doctest (#94) (@odow)
- Fix MethodError with unsupported layers in (F)lux (#95) (@odow)
- Add GrayBox predictor (#96) (@odow)
- Fix formatting in src/predictors/Scale.jl (#97) (@odow)
- Add test/test_PythonCall.jl (#98) (@odow)
- [docs] update sources of inspiration (#99) (@odow)
- Add Hessian support to GrayBox (#100) (@odow)
- [docs] fix doc build and avoid segfault via PythonCall (#103) (@odow)
- [docs] add DecisionTree tutorial, tweak other docs (#104) (@odow)
- Add a tutorial for Lux (#105) (@odow)
- [docs] minor tweaks to the documentation (#106) (@odow)
- s/Pytorch/PyTorch/ (#107) (@odow)
- Add tutorial for AbstractGPs (#108) (@odow)
- Add support for nn.Softplus layer in PyTorch (#111) (@odow)
- Add instructions for non-conda python environment (#113) (@Robbybp)
- Support `beta` parameter in SoftPlus (#114) (@Robbybp)
- Fix typo in SoftMax docs (#115) (@Robbybp)
- Tweak LICENSE to match wording from LANL (#117) (@odow)
- Add GitHub actions (#118) (@odow)
- Update README.md to mention project code (#119) (@odow)
- Clarify relationship to OMLT in README (#120) (@odow)
- Add documentation to CI (#121) (@odow)
- Run GitHub actions CI on pushes to main (#122) (@odow)
- Add badges to README (#123) (@odow)
- Add CODECOV_TOKEN to Github Actions (#124) (@odow)
- Build documentation on push to main (#125) (@odow)
- Add documentation link to the README (#126) (@odow)
- Make the tests less flakey (#128) (@odow)
- Improve code coverage (#129) (@odow)
- Improve code coverage (#130) (@odow)
- Add doc_cleanup to GitHub actions (#132) (@odow)
- Update tests to use Julia v1.11 (#133) (@odow)
- Update codecov badge in README (#134) (@odow)
- Remove explicit mention of Mo'ai (#135) (@odow)
- Install torch in GitHub actions (#136) (@odow)
- Add installation instructions to the README (#137) (@odow)
- Fix implied variable bounds in ReLU (#138) (@odow)

**Closed issues:**
- MVP planning (#1)
- Neural networks (#3)
- Logistic layer (#16)
- GLM.jl and DataFrames.jl (#27)
- Add a way to override layer choices (#35)
- Add GradientBoostedTrees (#43)
- Add GaussianProcess (#44)
- Tensorflow JSON (#65)
- [breaking] return config struct from each layer (#67)
- Add support for PyTorch (#68)
- Support reduced-space formulation (#70)
- Add a way to return predictor from extensions (#74)
- Doctests fail if CondaPkg is not installed (#75)
- Add OffsetScaling predictor (#87)
- [GrayBox] add Hessian support (#90)
- MOI Hessian evaluation is slow with reduced-space predictors (#102)
- Add soft plus layer for torch (#110)
- Threading and PyTorch (#116)
- Tests are flakey (#127)
- Add PyTorch to GitHub actions (#131)