Category: BayesianPage 2 of 7
I gave a talk on Title: Howtoproveyoursamplerisgood?#1 Findmetrictoproveconvergence slides: https://docs.google.com/presentation/d/1dLiLVRFKoisOKXfJ5dDZikOMxz51CIDsy4tGtrE-7HE/edit?usp=sharing
I gave a talk on hyperbolic space, its application in structure data, and how to design its sampler. The key lies in designing a metric and latent space….
The definition of reliability is the probability that a system will perform its intended function for a specified period of time under stated condition. Note that we are…
One of my academic goal is to establish a Bayesian risk management workflow in operations research, especially for the defense industry where I have great project opportunities through…
The current model in here is for prediction ie. the result is the optimal parameter value that minimizes the distance between prediction and real data. My goal is…
Justifications and recommendations complete pooling discarding a variance component or setting the variance to zero understates the uncertainty standard errors for coefficients of covariates that vary between groups…
Necessity of prior as common sense representation, especially when data cannot speak for themselves. Prior information is essential also for a different reason, if we are trying to…
I am trying to making stan’s advi engine more robust in terms of the following: stopping rule values returned from each iteration 1 is decided based on 2…
Based my interests, I have elaborated or summarized four areas from Gelman20. Bootstrapping and simulation-based inference We can enhance our sufficient statistics (Xbar) and sampling distribution (normal) by…
Posterior does not possess a closed form, as the move from the generative problem (the specification of p(y | θ)) to the inverse problem (the production of p(θ…