Releases: JuliaGaussianProcesses/BayesianLinearRegressors.jl
Releases · JuliaGaussianProcesses/BayesianLinearRegressors.jl
v0.3.8
v0.3.7
BayesianLinearRegressors v0.3.7
Closed issues:
- Store the cholesky of the precision matrix (#26)
- Add function samples section to readme (#31)
- Parametrizable non-linear feature mapping ϕ (#32)
Merged pull requests:
- Posterior closure under PDMat (#33) (@rossviljoen)
- Fix the main readme example and add function sampling example (#34) (@rossviljoen)
- Patch bump for #33 (#36) (@rossviljoen)
v0.3.6
BayesianLinearRegressors v0.3.6
Merged pull requests:
- RFC: Add feature mapping to BLR (#30) (@rossviljoen)
v0.3.5
BayesianLinearRegressors v0.3.5
Closed issues:
- Use the AbstractVectors convention for inputs instead of matrices (#25)
Merged pull requests:
- Run JuliaFormatter and add CI (#27) (@rossviljoen)
- Fix CI tests (#28) (@rossviljoen)
- Vector Inputs (#29) (@willtebbutt)
v0.3.4
BayesianLinearRegressors v0.3.4
Closed issues:
- Sampling Functions (#22)
Merged pull requests:
- fix some spelling in README (#23) (@st--)
- Drawing function samples (#24) (@rossviljoen)
v0.3.3
BayesianLinearRegressors v0.3.3
Merged pull requests:
- CompatHelper: bump compat for AbstractGPs to 0.5, (keep existing compat) (#21) (@github-actions[bot])
v0.3.2
BayesianLinearRegressors v0.3.2
Merged pull requests:
- Utilise test utils (#16) (@willtebbutt)
- CompatHelper: bump compat for "AbstractGPs" to "0.4" (#17) (@github-actions[bot])
v0.3.1
BayesianLinearRegressors v0.3.1
v0.3.0
BayesianLinearRegressors v0.3.0
Merged pull requests:
- Use github CI (#11) (@willtebbutt)
- Remove Windows CI (#12) (@willtebbutt)
- Move to AbstractGPs API (#13) (@willtebbutt)
v0.2.2
BayesianLinearRegressors v0.2.2
Merged pull requests: