Releases: stefan-m-lenz/BoltzmannMachines.jl
Releases · stefan-m-lenz/BoltzmannMachines.jl
v1.3.0
New features:
- The
batchsize
can be specified also for fine tuning infitdbm
andtraindbm!
. The batchsize can be specified seperately for fine tuning and pretraining via the argumentsbatchsizefinetuning
(new) andbatchsizepretraining
infitdbm
. - Added function
top2latentdims
, enabling a convenient dimension reduction with DBMs - Added a new example for using DBMs for dimension reduction
- Added function
blocksinnoise
, simulating data sets with different subgroups and labels - Migrated continuous integration from Travis CI to GitHub Actions
Bug fix:
- Argument
optimizerpretraining
infitdbm
is now respected. (Previously only theoptimizer
argument was used.)
Deprecation:
- Argument
learningrates
infitdbm
is renamed tolearningratesfinetuning
for clarity
v1.2.0
- More convenient monitoring with the functions
monitored_fitrbm
,monitored_stackrbms
,monitored_traindbm!
andmonitored_fitdbm
- Added functions
intensities_encode
andintensities_decode
to transform continuous data into the interval [0,1] and back - Added examples for using
Softmax0BernoulliRBM
s - Added examples for using partitioned layers in
MultimodalDBM
s - Compatibility with the JuliaConnectoR: Avoid using copies of anonymous functions when preparing the
TrainLayers
- For reproducibility, the RBMs in partitioned layers are not trained in parallel processes any more when Julia runs multiple processes
- Fixed documentation of
splitdata
- Other small improvements in the documentation
- Removed dependency on "Distributions": BoltzmannMachines is now only depending on packages in stdlib.
v1.1.0
New features:
- Modelling categorical data in RBMs and DBMs using the new type of
Softmax0BernoulliRBM
s (complete with likelihood monitoring) - Conditional sampling via
gibbssamplecond!
andsamples
(see examples) - Data preprocessing functions:
intensities
,oneornone_encode
Other changes:
- Longer default burnin when estimating the
empiricalloglikelihood
- Removed deprecated function
addlayer!
v1.0.1
Fixes issues in monitoring multimodal DBMs and in logproblowerbound
v1.0.0
Upgrade to Julia 1.0
Added Travis CI testing
v0.1.0
First version for official release