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Christopher Paciorek edited this page
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Topics
Tips for avoiding errors in nimbleFunction programming and compilation (DSL)
Bayesian nonparametrics
Developer manuals and tutorials
We've just started putting bits of content into a
NIMBLE Developer Guide
.
Random tips and tricks
MCMC Style Guide
MCMC Vignettes
BYU Workshop Tutorials
Experimental features
Using Tensorflow as a back end
Wiki pages
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35
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Home
Topics
Developer manuals and tutorials
Experimental features
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Automatic differentiation in NIMBLE
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Bayesian nonparametrics
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Calibrated Posterior Predictive P values
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Compiler steps for an RCfunction (or nimbleFunction class method)
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Cross validation
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Defining a new distribution in NIMBLE
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Design Doc: Derivatives of distributions
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Design Doc: Saving, loading, and related redesigns
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Design Doc: support optim() and optimize()
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Design Doc: Tensorflow as a backend
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Design Doc: vectorizing model operations
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Design ideas for nimbleList and more
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Design of type declarations and object creation
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Developer backdoor to manually replace generated C
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dynamic indexing BUGS processing
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geoNimble
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how to reuse a simple nimbleFunction outside of nimble
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Ideas for outreach examples tutorials website content
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MCMC Style Guide
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Model Macros
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Multivariate normal conjugacy
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NIMBLE compiler
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NIMBLE design questions
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NIMBLE Developer Guide
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NIMBLE function compilation flow
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Node query processing steps
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Pivoted Cholesky
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Planning dynamic indexing implementation
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Random tips and tricks
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Steps in processing BUGS code
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stochastic indexing
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Summary of core R features implemented Fall 2016
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Tips for avoiding errors in nimbleFunction programming and compilation (DSL)
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Using Tensorflow as a back end
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