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Increasing Interpretability of Bayesian Probabilistic Programming Models Through Interactive Representations (2020)

First Author: Taka E

Attributed to: Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.3389/fcomp.2020.567344

Publication URI: http://dx.doi.org/10.3389/fcomp.2020.567344

Type: Journal Article/Review

Parent Publication: Frontiers in Computer Science