10 citations · 56 across the 19 of their papers we have counts for
6 papers · 1 filter
Hybrid Bayesian network discovery with latent variables by scoring multiple interventions
Kiattikun Chobtham, Anthony C. Constantinou, Neville K. Kitson
In Bayesian Networks (BNs), the direction of edges is crucial for causal reasoning and inference. However, Markov equivalence class considerations mean it is not always possible to…
Effective and efficient structure learning with pruning and model averaging strategies
Anthony C. Constantinou, Yang Liu, Neville K. Kitson +2
Learning the structure of a Bayesian Network (BN) with score-based solutions involves exploring the search space of possible graphs and moving towards the graph that maximises a gi…
A survey of Bayesian Network structure learning
Neville K. Kitson, Anthony C. Constantinou, Zhigao Guo +2
Bayesian Networks (BNs) have become increasingly popular over the last few decades as a tool for reasoning under uncertainty in fields as diverse as medicine, biology, epidemiology…
Greedy structure learning from data that contain systematic missing values
Yang Liu, Anthony C. Constantinou
Learning from data that contain missing values represents a common phenomenon in many domains. Relatively few Bayesian Network structure learning algorithms account for missing dat…
How do some Bayesian Network machine learned graphs compare to causal knowledge?
Anthony C. Constantinou, Norman Fenton, Martin Neil
The graph of a Bayesian Network (BN) can be machine learned, determined by causal knowledge, or a combination of both. In disciplines like bioinformatics, applying BN structure lea…
The impact of prior knowledge on causal structure learning
Anthony C. Constantinou, Zhigao Guo, Neville K. Kitson
Causal Bayesian networks have become a powerful technology for reasoning under uncertainty in areas that require transparency and explainability, by relying on causal assumptions t…