4 papers · 1 filter
LLM-Augmented Causal Discovery: Probabilistic Fusion of Edge Existence and Orientation
Neville K. Kitson, Anthony Constantinou
Bayesian network structure learning (BNSL) from observational data struggles with orientation identifiability, while large language models (LLMs) offer broad but often unreliable c…
Using GPT-4 to guide causal machine learning
Anthony C. Constantinou, Neville K. Kitson, Alessio Zanga
Since its introduction to the public, ChatGPT has had an unprecedented impact. While some experts praised AI advancements and highlighted their potential risks, others have been cr…
Causal discovery using dynamically requested knowledge
Neville K Kitson, Anthony C Constantinou
Causal Bayesian Networks (CBNs) are an important tool for reasoning under uncertainty in complex real-world systems. Determining the graphical structure of a CBN remains a key chal…
Learning Bayesian networks from demographic and health survey data
Neville Kenneth Kitson, Anthony C. Constantinou
Child mortality from preventable diseases such as pneumonia and diarrhoea in low and middle-income countries remains a serious global challenge. We combine knowledge with available…