This paper is an exploration in a functional programming framework of isomorphisms between elementary data types (natural numbers, sets, finite functions, permutations binary deci...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
— Bayesian networks have extensively been used in numerous fields including artificial intelligence, decision theory and control. Its ability to utilize noisy and missing data ...
Thanura R. Elvitigala, Abhay K. Singh, Himadri B. ...
Computing methods that allow the efficient and accurate processing of experimentally gathered data play a crucial role in biological research. The aim of this paper is to present a...
This paper describes a new approach to unify constraints on parameters with training data to perform parameter estimation in Bayesian networks of known structure. The method is ge...