1 citations · 1 across the 2 of their papers we have counts for
3 papers
stat.ML2025
Amortized Conditional Independence Testing
Bao Duong, Nu Hoang, Thin Nguyen
Testing for the conditional independence structure in data is a fundamental and critical task in statistics and machine learning, which finds natural applications in causal discove…
cs.LG2024★ 1 cited
Scalable Variational Causal Discovery Unconstrained by Acyclicity
Nu Hoang, Bao Duong, Thin Nguyen
Bayesian causal discovery offers the power to quantify epistemic uncertainties among a broad range of structurally diverse causal theories potentially explaining the data, represen…
cs.LG2024
Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows
Nu Hoang, Bao Duong, Thin Nguyen
Post-nonlinear (PNL) causal models stand out as a versatile and adaptable framework for modeling intricate causal relationships. However, accurately capturing the invertibility con…