1 citations · 1 across the 11 of their papers we have counts for
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Tractable Approximation of Labeled Multi-Object Posterior Densities
Thi Hong Thai Nguyen, Ba-Ngu Vo, Ba-Tuong Vo
Multi-object estimation in state-space models (SSMs) wherein the system state is represented as a finite set has attracted significant interest in recent years. In Bayesian inferen…
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…
Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
Khoa Nguyen, Viet Huynh, Binh Tran +3
Bayesian Optimization (BO) is a well-established method for addressing black-box optimization problems. In many real-world scenarios, optimization often involves multiple functions…
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…
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…