Results 11 to 20 of about 455,494 (313)
Quantitative Causality, Causality-Aided Discovery, and Causal Machine Learning
Ocean-Land-Atmosphere Research, 2023 It has been said, arguably, that causality analysis should pave a promising way to interpretable deep learning and generalization. Incorporation of causality into artificial intelligence algorithms, however, is challenged with its vagueness, nonquantitativeness, computational inefficiency, etc.
Xin‐Zhong Liang +2 more
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Causal Factors, Causal Inference, Causal Explanation [PDF]
Aristotelian Society Supplementary Volume, 1986 s from how likely it is that the person is a smoker in the first place. More generally, the trouble is that the likelihood principle aims to by-pass decisions about prior probabilities. Perhaps there are some inferential contexts where such decisions can sensibly be avoided. But the inference from Harry's heart attack to his smoking isn't one of them. (
Elliott Sober, David Papineau
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Causality, Causal Discovery, and Causal Inference in Structural Engineering
CoRR, 2022 Much of our experiments are designed to uncover the cause(s) and effect(s) behind a data generating mechanism (i.e., phenomenon) we happen to be interested in. Uncovering such relationships allows us to identify the true working of a phenomenon and, most importantly, articulate a model that may enable us to further explore the phenomenon on hand and/or
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Distinguishing causality principles [PDF]
, 2012 We distinguish two sub-types of each of the two causality principles formulated in connection with the Common Cause Principle in Henson (2005) and raise and investigate the problem of logical relations among the resulting four causality principles. Based
Rédei, Miklós, San Pedro, Iñaki
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Causal Inference with Deep Causal Graphs
CoRR, 2020 Supplementary material can be found in https://github.com/aparafita/dcg ...
Álvaro Parafita, Jordi Vitrià
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Frontiers in Public Health, 2023 This paper estimates the effect of antibiotic usage in humans and food-producing animals on the prevalence of resistance in zoonotic bacteria in both humans and animals. Using comprehensive longitudinal data from annual surveillance reports on resistance
Sakib Rahman, Aidan Hollis
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Causal KL: Evaluating Causal Discovery
CoRR, 2021 26 ...
Rodney T. O'Donnell +2 more
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K-Causality Coincides with Stable Causality [PDF]
Communications in Mathematical Physics, 2009 It is proven that K-causality coincides with stable causality, and that in a K-causal spacetime the relation K^+ coincides with the Seifert's relation. As a consequence the causal relation "the spacetime is strongly causal and the closure of the causal relation is transitive" stays between stable causality and causal continuity.
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St Andrews Encyclopaedia of Theology, 2023 Causality is a central concept in philosophy and theology and also a basic aspect of human thought and speech. Causal words such as ‘making’, ‘doing’, ‘producing’, and so on, are in constant use.
Michael J. Dodds O.P.
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Causal-learn: Causal Discovery in Python
J. Mach. Learn. Res., 2023 Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe $\textit{causal-learn}$, an open-source Python library for causal discovery. This library focuses on bringing a comprehensive collection of causal discovery methods to both practitioners and researchers.
Yujia Zheng 0001 +8 more
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