Heteroscedastic Causal Structure Learning

B Duong, T Nguyen - ECAI 2023, 2023 - ebooks.iospress.nl
Heretofore, learning the directed acyclic graphs (DAGs) that encode the cause-effect
relationships embedded in observational data is a computationally challenging problem. A …

Diffeomorphic information neural estimation

B Duong, T Nguyen - Proceedings of the AAAI Conference on Artificial …, 2023 - ojs.aaai.org
Abstract Mutual Information (MI) and Conditional Mutual Information (CMI) are multi-purpose
tools from information theory that are able to naturally measure the statistical dependencies …

Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax

I Butakov, A Sememenko, A Tolmachev… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep InfoMax (DIM) is a well-established method for self-supervised representation learning
(SSRL) based on maximization of the mutual information between the input and the output of …

Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows

N Hoang, B Duong, T Nguyen - arXiv preprint arXiv:2407.04980, 2024 - arxiv.org
Post-nonlinear (PNL) causal models stand out as a versatile and adaptable framework for
modeling intricate causal relationships. However, accurately capturing the invertibility …