Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Abstract: This work presents a novel posterior inference method for models with intractable evidence and likelihood functions. Error-guided likelihood-free MCMC, or EG-LF-MCMC in short, has been ...

Further from an earlier issue I posted (which was user error), I thought I would try out a few of the other likelihoods for a simple toy model, just so that I know what I am doing in the future. The ...

Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning ...

BOSTON, June 11 /PRNewswire/ -- MCMC LLC (MCMC) announced today that its Peer Review Analysis(R) (PRA(R)) and Medical Care Ombudsman (MCOP) programs have been awarded Independent Review Organization ...