Masterthesis

The following packages were used:

1. [6710c13c] AutoGrad v1.2.5 https://github.com/denizyuret/AutoGrad.jl.git#master
2. [336ed68f] CSV v0.10.4
3. [052768ef] CUDA v3.10.0
4. [a93c6f00] DataFrames v1.3.4
5. [5789e2e9] FileIO v1.14.0
6. [f67ccb44] HDF5 v0.16.10
7. [7073ff75] IJulia v1.23.3
8. [033835bb] JLD2 v0.4.22
9. [1902f260] Knet v1.4.10
10. [eb30cadb] MLDatasets v0.5.16
11. [b9e938e5] NNHelferlein v1.1.1 https://github.com/KnetML/NNHelferlein.jl.git#main
12. [8314cec4] PGFPlotsX v1.5.0
13. [eadc2687] Pandas v1.5.3
14. [f0f68f2c] PlotlyJS v0.18.8
15. [91a5bcdd] Plots v1.29.0
16. [438e738f] PyCall v1.93.1
17. [295af30f] Revise v3.3.3
18. [28f6a940] TensorFlow v0.12.0 https://github.com/malmaud/TensorFlow.jl.git#master

Make sure to install all with julia package manager

The structure of the repository:

1. loaddata.ipynb -> preparing the genexpression data and the metadata
2. VAE.ipynb -> training the VAE
3. MLPAE -> training the MLP plus the AE