Integrating AbstractMCMC and fixing predictions (#93)

* Started adding AbstractMCMC sampling

* Removed part in training.jl

* Fixed the predictions

* Fixing docs

* Update bayesiansvm.jl

* Update logistic.jl

* Update gibbssampling.jl

* Update make.jl

* Correct formatting and tests

* Fix MCVI (maybe?)

* Improve the docs

* Fix some mroe tests

* Fixed EVEN more bugs

Author: theogf

Project.toml

@@ -1,21 +1,19 @@
 name = "AugmentedGaussianProcesses"
 uuid = "38eea1fd-7d7d-5162-9d08-f89d0f2e271e"
 authors = ["Theo Galy-Fajou <[email protected]>"]
-version = "0.10.1"
+version = "0.10.2"
 
 [deps]
+AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 AdvancedHMC = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
-Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 FastGaussQuadrature = "442a2c76-b920-505d-bb47-c5924d526838"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 InducingPoints = "b4bd816d-b975-4295-ac05-5f2992945579"
 KernelFunctions = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
@@ -28,16 +26,15 @@ StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
+AbstractMCMC = "2"
 AdvancedHMC = "0.2.13"
 ChainRulesCore = "0.9"
-Distances = "0.8, 0.9, 0.10"
 Distributions = "0.21.5, 0.22, 0.23, 0.24"
 FastGaussQuadrature = "0.4"
 Flux = "0.10, 0.11, 0.12"
 ForwardDiff = "0.10"
 InducingPoints = "0.1"
 KernelFunctions = "0.8, 0.9"
-MCMCChains = "0.3.15, 2.0, 3.0, 4.0"
 ProgressMeter = "1"
 RecipesBase = "1.0, 1.1"
 Reexport = "0.2, 1"