1 citations · 3 across the 5 of their papers we have counts for
5 papers
Domain Generalisation via Risk Distribution Matching
Toan Nguyen, Kien Do, Bao Duong +1
We propose a novel approach for domain generalisation (DG) leveraging risk distributions to characterise domains, thereby achieving domain invariance. In our findings, risk distrib…
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Quang-Duy Tran, Phuoc Nguyen, Bao Duong +1
Score-based approaches in the structure learning task are thriving because of their scalability. Continuous relaxation has been the key reason for this advancement. Despite achievi…
Heteroscedastic Causal Structure Learning
Bao Duong, Thin Nguyen
Heretofore, learning the directed acyclic graphs (DAGs) that encode the cause-effect relationships embedded in observational data is a computationally challenging problem. A recent…
Conditional Independence Testing via Latent Representation Learning
Bao Duong, Thin Nguyen
Detecting conditional independencies plays a key role in several statistical and machine learning tasks, especially in causal discovery algorithms. In this study, we introduce LCIT…
Efficient Classification with Counterfactual Reasoning and Active Learning
Azhar Mohammed, Dang Nguyen, Bao Duong +1
Data augmentation is one of the most successful techniques to improve the classification accuracy of machine learning models in computer vision. However, applying data augmentation…