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cs.LG2025
Identifying Causal Direction via Variational Bayesian Compression
Quang-Duy Tran, Bao Duong, Phuoc Nguyen +1
Telling apart the cause and effect between two random variables with purely observational data is a challenging problem that finds applications in various scientific disciplines. A…
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.LG2025
Causal Discovery via Bayesian Optimization
Bao Duong, Sunil Gupta, Thin Nguyen
Existing score-based methods for directed acyclic graph (DAG) learning from observational data struggle to recover the causal graph accurately and sample-efficiently. To overcome t…