1 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
From Observations to Causations: A GNN-based Probabilistic Prediction Framework for Causal Discovery
Rezaur Rashid, Gabriel Terejanu
Causal discovery from observational data is challenging, especially with large datasets and complex relationships. Traditional methods often struggle with scalability and capturing…
Evaluation of Induced Expert Knowledge in Causal Structure Learning by NOTEARS
Jawad Chowdhury, Rezaur Rashid, Gabriel Terejanu
Causal modeling provides us with powerful counterfactual reasoning and interventional mechanism to generate predictions and reason under various what-if scenarios. However, causal…
From Causal Pairs to Causal Graphs
Rezaur Rashid, Jawad Chowdhury, Gabriel Terejanu
Causal structure learning from observational data remains a non-trivial task due to various factors such as finite sampling, unobserved confounding factors, and measurement errors.…
Explainable Deep Modeling of Tabular Data using TableGraphNet
Gabriel Terejanu, Jawad Chowdhury, Rezaur Rashid +1
The vast majority of research on explainability focuses on post-explainability rather than explainable modeling. Namely, an explanation model is derived to explain a complex black…