Identifiability of direct effects from summary causal graphs
S Ferreira, CK Assaad - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
Dynamic structural causal models (SCMs) are a powerful framework for reasoning in
dynamic systems about direct effects which measure how a change in one variable affects …
dynamic systems about direct effects which measure how a change in one variable affects …
On the Fly Detection of Root Causes from Observed Data with Application to IT Systems
This paper introduces a new structural causal model tailored for representing threshold-
based IT systems and presents a new algorithm designed to rapidly detect root causes of …
based IT systems and presents a new algorithm designed to rapidly detect root causes of …
Toward identifiability of total effects in summary causal graphs with latent confounders: an extension of the front-door criterion
CK Assaad - arXiv preprint arXiv:2406.05805, 2024 - arxiv.org
Conducting experiments to estimate total effects can be challenging due to cost, ethical
concerns, or practical limitations. As an alternative, researchers often rely on causal graphs …
concerns, or practical limitations. As an alternative, researchers often rely on causal graphs …
[PDF][PDF] Causal Temporal Regime Structure Learning
A Rahmani, P Frossard - researchgate.net
We address the challenge of structure learning from multivariate time series that are
characterized by a sequence of different, unknown regimes. We introduce a new …
characterized by a sequence of different, unknown regimes. We introduce a new …