Zobrazeno 1 - 10
of 1 365
pro vyhledávání: '"Causal discovery"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Developing machine learning (ML) methods for healthcare predictive modeling requires absolute explainability and transparency to build trust and accountability. Graphical models (GM) are key tools for this but face challenges like small samp
Externí odkaz:
https://doaj.org/article/bb610cb66ef442a1a76b093177e12549
Publikováno v:
Journal of Causal Inference, Vol 12, Iss 1, Pp 278-85 (2024)
Discovering causal relationships from observational data is a challenging task that relies on assumptions connecting statistical quantities to graphical or algebraic causal models. In this work, we focus on widely employed assumptions for causal disc
Externí odkaz:
https://doaj.org/article/cd654148a66d44148aba5b1f410cc0b3
Autor:
Nicolas Alexander Schulz, Jasmin Carus, Alexander Johannes Wiederhold, Ole Johanns, Frederik Peters, Natalie Rath, Katharina Rausch, Bernd Holleczek, Alexander Katalinic, the AI-CARE Working Group, Christopher Gundler
Publikováno v:
BMC Medical Research Methodology, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Generating synthetic patient data is crucial for medical research, but common approaches build up on black-box models which do not allow for expert verification or intervention. We propose a highly available method which enables s
Externí odkaz:
https://doaj.org/article/dec1b1d848d74098abd187748b4ee6cc
Publikováno v:
NeuroImage, Vol 297, Iss , Pp 120684- (2024)
Understanding the complex mechanisms of the brain can be unraveled by extracting the Dynamic Effective Connectome (DEC). Recently, score-based Directed Acyclic Graph (DAG) discovery methods have shown significant improvements in extracting the causal
Externí odkaz:
https://doaj.org/article/68de578965984dbfa57a50ad7388276f
Publikováno v:
IEEE Access, Vol 12, Pp 136502-136514 (2024)
In causal learning, discovering the causal graph of the underlying generative mechanism from observed data is crucial. However, real-world data for causal discovery is scarce and expensive, leading researchers to rely on synthetic datasets, which may
Externí odkaz:
https://doaj.org/article/0d9c60d322634aca864dcaa6e72f88f9
Publikováno v:
IEEE Access, Vol 12, Pp 33057-33068 (2024)
Causal discovery is the process of modeling cause and effect relationships among features. Unlike traditional model-based approaches, that rely on fitting data to the models, methods of causal discovery determine the causal structure from data. In cl
Externí odkaz:
https://doaj.org/article/991a131e259848eb9adfac4ceb813493
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 5, Pp 393-401 (2024)
We introduce Dagma-DCE, an interpretable and model-agnostic scheme for differentiable causal discovery. Current non- or over-parametric methods in differentiable causal discovery use opaque proxies of “independence” to justify the inclusion or ex
Externí odkaz:
https://doaj.org/article/f4ae1f02b2dd4acb82f3205acd051a9f
Autor:
De Souter Luna
Publikováno v:
Journal of Causal Inference, Vol 12, Iss 1, Pp 239-71 (2024)
Configurational Comparative Methods (CCMs) aim to learn causal structures from datasets by exploiting Boolean sufficiency and necessity relationships. One important challenge for these methods is that such Boolean relationships are often not satisfie
Externí odkaz:
https://doaj.org/article/fabe49ffb7d746789a435fb7fec3e7e8
Autor:
Shi Bo, Minheng Xiao
Publikováno v:
Algorithms, Vol 17, Iss 11, p 498 (2024)
Managing delivery risks is a critical challenge in modern supply chain management due to the increasing complexity and interdependencies of global supply networks. Existing methods often rely on correlation-based approaches, which fail to uncover the
Externí odkaz:
https://doaj.org/article/ae589b4b1a6743a588b0b41c14c48dea
Publikováno v:
Symmetry, Vol 16, Iss 11, p 1551 (2024)
With the continuous development of network security situations, the types of attacks increase sharply, but can be divided into symmetric attacks and asymmetric attacks. Symmetric attacks such as phishing and DDoS attacks exploit fixed patterns, resul
Externí odkaz:
https://doaj.org/article/68bcd61a7286401593d54e81ec91572b