Results 121 to 130 of about 971,523 (344)
Estimating complex causal effects from incomplete observational data [PDF]
arXiv, 2014 Despite the major advances taken in causal modeling, causality is still an unfamiliar topic for many statisticians. In this paper, it is demonstrated from the beginning to the end how causal effects can be estimated from observational data assuming that the causal structure is known.
arxiv
Actual causation and the art of modeling [PDF]
, 2010 We look more carefully at the modeling of causality using structural equations. It is clear that the structural equations can have a major impact on the conclusions we draw about causality. In particular, the choice of variables and their values can also
Halpern, Joseph Y. +1 more
core +2 more sources
International Journal of Adaptive Control and Signal Processing, EarlyView.The cost as a function of the number of experiments for a non‐symmetric 21×21$$ 21\times 21 $$ system. Four approaches are shown: the proposed stochastic conjugate gradient ILC (SCGILC) method (), deterministic conjugate gradient ILC (), stochastic gradient descent ILC () and deterministic gradient descent ILC ().
Leontine Aarnoudse, Tom Oomen
wiley +1 more source
Strong Cosmic Censorship and Causality Violation
, 1997 We investigate the instability of the Cauchy horizon caused by causality violation in the compact vacuum universe with the topology $B\times {\bf S}^{1}\times {\bf R}$, which Moncrief and Isenberg considered.
A. Ishibashi +24 more
core +1 more source
The Regulation of Trace Metal Elements in Cancer Ferroptosis
Advanced Biology, EarlyView.The induction of ferroptosis inhibits tumor growth, enhances anticancer efficacy, and overcomes drug resistance. Recent evidence shows nonferrous metal elements play a role in ferroptosis. This review focuses on how trace metals regulate ferroptosis processes like iron accumulation, lipid peroxidation, and antioxidant defense.
Xiaoyan Wang +5 more
wiley +1 more source
arXiv, 2016 We propose a new method of discovering causal relationships in temporal data based on the notion of causal compression. To this end, we adopt the Pearlian graph setting and the directed information as an information theoretic tool for quantifying causality. We introduce chain rule for directed information and use it to motivate causal sparsity. We show
arxiv
Causality, causality, causality: the view of education inputs and outputs from economics [PDF]
Educators and policy makers are increasingly intent on using scientifically-based evidence when making decisions about education policy. Thus, education research today must necessarily be focused on identifying the causal relationships between education ...
Cecilia Elena Rouse, Lisa Barrow
core
A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion
Advanced Engineering Materials, EarlyView.A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann +5 more
wiley +1 more source
Challenges of Using Text Classifiers for Causal Inference [PDF]
arXiv, 2018 Causal understanding is essential for many kinds of decision-making, but causal inference from observational data has typically only been applied to structured, low-dimensional datasets. While text classifiers produce low-dimensional outputs, their use in causal inference has not previously been studied.
arxiv
Education and myopia: assessing the direction of causality by mendelian randomisation
British medical journal, 2018 Objectives To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. Design Bidirectional, two sample mendelian randomisation study.
Edward Mountjoy +7 more
semanticscholar +1 more source