Search Results for author:
Found 8 papers, 0 papers with code
Tuning structure learning algorithms with out-of-sample and resampling strategies
One of the challenges practitioners face when applying structure learning algorithms to their data involves determining a set of hyperparameters; otherwise, a set of hyperparameter defaults is assumed.
Open problems in causal structure learning: A case study of COVID-19 in the UK
Causal machine learning (ML) algorithms recover graphical structures that tell us something about cause-and-effect relationships.
Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound
Discovering and parameterising latent confounders represent important and challenging problems in causal structure learning and density estimation respectively.
Hybrid Bayesian network discovery with latent variables by scoring multiple interventions
The algorithm assumes causal insufficiency in the presence of latent variables and produces a Partial Ancestral Graph (PAG).
Effective and efficient structure learning with pruning and model averaging strategies
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 given objective function.
A survey of Bayesian Network structure learning
This paper provides a comprehensive review of combinatoric algorithms proposed for learning BN structure from data, describing 74 algorithms including prototypical, well-established and state-of-the-art approaches.
Bayesian network structure learning with causal effects in the presence of latent variables
Structure learning algorithms that assume causal insufficiency tend to reconstruct the ancestral graph of a BN, where bi-directed edges represent confounding and directed edges represent direct or ancestral relationships.
Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data
This paper investigates the performance of 15 structure learning algorithms.
