1 citations · 2 across the 3 of their papers we have counts for
4 papers
Beyond Conditional Independence: Root Cause Analysis with Deep Causal Models
Md Musfiqur Rahman, Kenneth Lee, Ziwei Jiang +3
Root cause analysis (RCA) is a critical problem in many real-world scenarios. RCA enables the identification of faulty or failing mechanisms in a system by comparing anomalous obse…
Uncertainty-aware Causal Decision Making via Effect Bound Decomposition
Md Musfiqur Rahman, Ziwei Jiang, Hilaf Hasson +1
Causal inference from observational data can provide strong evidence for finding the best action in a decision-making scenario without having to perform expensive randomized trials…
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand
Md Musfiqur Rahman, Matt Jordan, Murat Kocaoglu
Causal inference from observational data plays critical role in many applications in trustworthy machine learning. While sound and complete algorithms exist to compute causal effec…
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
Sound and complete algorithms have been proposed to compute identifiable causal queries using the causal structure and data. However, most of these algorithms assume accurate estim…