Methods and tools for causal discovery and causal inference

AR Nogueira, A Pugnana, S Ruggieri… - … reviews: data mining …, 2022 - Wiley Online Library
Causality is a complex concept, which roots its developments across several fields, such as
statistics, economics, epidemiology, computer science, and philosophy. In recent years, the …

Evaluation methods and measures for causal learning algorithms

L Cheng, R Guo, R Moraffah, P Sheth… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The convenient access to copious multifaceted data has encouraged machine learning
researchers to reconsider correlation-based learning and embrace the opportunity of …

Causal machine learning: A survey and open problems

J Kaddour, A Lynch, Q Liu, MJ Kusner… - ar** optimal causal cyber-defence agents via cyber security simulation
A Andrew, S Spillard, J Collyer, N Dhir - arxiv preprint arxiv:2207.12355, 2022 - arxiv.org
In this paper we explore cyber security defence, through the unification of a novel cyber
security simulator with models for (causal) decision-making through optimisation. Particular …

Estimating possible causal effects with latent variables via adjustment

TZ Wang, T Qin, ZH Zhou - International Conference on …, 2023 - proceedings.mlr.press
Causal effect identification is a fundamental task in artificial intelligence. A most ideal
scenario for causal effect identification is that there is a directed acyclic graph as a prior …