CAnDOIT: Causal Discovery with Observational and Interventional Data from Time Series
L Castri, S Mghames, M Hanheide… - Advanced Intelligent …, 2024 - Wiley Online Library
The study of cause and effect is of the utmost importance in many branches of science, but
also for many practical applications of intelligent systems. In particular, identifying causal …
also for many practical applications of intelligent systems. In particular, identifying causal …
Bayesian optimization of expensive nested grey-box functions
We consider the problem of optimizing a grey-box objective function, ie, nested function
composed of both black-box and white-box functions. A general formulation for such grey …
composed of both black-box and white-box functions. A general formulation for such grey …
[HTML][HTML] Design of Optimal Intervention Based on a Generative Structural Causal Model
H Wu, S Chen, J Fan, G Jin - Mathematics, 2024 - mdpi.com
In the industrial sector, malfunctions of equipment that occur during the production and
operation process typically necessitate human intervention to restore normal functionality …
operation process typically necessitate human intervention to restore normal functionality …
Optimizing Causal Interventions in Hybrid Bayesian Networks: A Discretization, Knowledge Compilation, and Heuristic Optimization Approach
Causality is increasingly integrated into decision-making processes. Often, the goal is to
optimize over causal interventions to achieve specific policy objectives. However, research …
optimize over causal interventions to achieve specific policy objectives. However, research …
Optimizing Causal Interventions in Hybrid Bayesian Networks
Causality is increasingly integrated into decision-making processes. Often, the goal is to
optimize over causal interventions to achieve specific policy objectives. However, research …
optimize over causal interventions to achieve specific policy objectives. However, research …
Structural and statistical uncertainty in observational causal machine learning at scale
A Jesson - 2023 - ora.ox.ac.uk
Causal machine learning (Causal ML) tackles various tasks, including causal-effect
inference, causal reasoning, and causal structure discovery. This thesis explores uncertainty …
inference, causal reasoning, and causal structure discovery. This thesis explores uncertainty …