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Fix for Zygote FluxML/Zygote.jl#717 included.
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femtomc committed Aug 25, 2020
1 parent d373a56 commit 086585d
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2 changes: 2 additions & 0 deletions docs/franklin/Project.toml
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Expand Up @@ -4,7 +4,9 @@ AdvancedHMC = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
Franklin = "713c75ef-9fc9-4b05-94a9-213340da978e"
GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
Jaynes = "a2015381-cef8-4fe1-827c-95a77dd17ccf"
Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
MCMCChains = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
NodeJS = "2bd173c7-0d6d-553b-b6af-13a54713934c"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
Pluto = "c3e4b0f8-55cb-11ea-2926-15256bba5781"
StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
33 changes: 0 additions & 33 deletions docs/franklin/_assets/scripts/bayeslinreg.jl

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2 changes: 0 additions & 2 deletions docs/franklin/_assets/scripts/output/bayeslinreg_3.txt

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8 changes: 4 additions & 4 deletions docs/franklin/notebooks.md
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Expand Up @@ -2,10 +2,10 @@

Here are a number of notebooks which explore common models, modeling idioms, and usage of the inference library.

* [Bayesian linear regression (with HMC and AdvancedHMC inference)](../notebooks/bayeslinreg)
* [Bayesian linear regression (with HMC and AdvancedHMC inference)](../bayeslinreg)

* [Gaussian mixture models (with custom kernels and automatic differentiation variational inference)](../notebooks/gmm)
* [Gaussian mixture models (with custom kernels and automatic differentiation variational inference)](../gmm)

* [Bayesian Lotka-Volterra (with AdvancedHMC inference)](../notebooks/blotka)
* [Bayesian Lotka-Volterra (with AdvancedHMC inference)](../blotka)

* [Hidden Markov model with multi-variate transition and observation (with programmable particle filtering)](../notebooks/hmm)
* [Hidden Markov model with multi-variate transition and observation (with programmable particle filtering)](../hmm)
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88 changes: 0 additions & 88 deletions docs/franklin/notebooks/gmm.md

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1 change: 0 additions & 1 deletion src/language_extensions/mcmc_chains.jl
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Expand Up @@ -4,7 +4,6 @@ macro load_chains()
@info "Loading diagnostic interface to \u001b[3m\u001b[34;1mMCMCChains.jl\u001b[0m\n\n \u001b[34;1mhttps://github.com/TuringLang/MCMCChains.jl\n\n "
try
using MCMCChains
using GR
using StatsPlots
using Random
catch
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