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pro vyhledávání: '"HENCKEL, P"'
The implication problem for conditional independence (CI) asks whether the fact that a probability distribution obeys a given finite set of CI relations implies that a further CI statement also holds in this distribution. This problem has a long and
Externí odkaz:
http://arxiv.org/abs/2404.05306
Evaluating graphs learned by causal discovery algorithms is difficult: The number of edges that differ between two graphs does not reflect how the graphs differ with respect to the identifying formulas they suggest for causal effects. We introduce a
Externí odkaz:
http://arxiv.org/abs/2402.08616
We propose an easy-to-use adjustment estimator for the effect of a treatment based on observational data from a single (social) network of units. The approach allows for interactions among units within the network, called interference, and for observ
Externí odkaz:
http://arxiv.org/abs/2312.02717
Publikováno v:
3D Printing in Medicine, Vol 10, Iss 1, Pp 1-11 (2024)
Abstract Background The Trident II Tritanium acetabular shell is additively manufactured (3D printed), based on the established Trident ‘I’ Tritanium shell, produced using conventional methods; this study characterised their differences. Methods
Externí odkaz:
https://doaj.org/article/0f543e4635594360877c1781c84e665e
Publikováno v:
EFORT Open Reviews, Vol 9, Iss 9, Pp 862-872 (2024)
Three-dimensional printing is a rapidly growing manufacturing method for orthopaedic implants and it is currently thriving in several other engineering industries. It enables the variation of implant design and the construction of complex structures
Externí odkaz:
https://doaj.org/article/93bc1d85218b44dd8c50546245fccef6
We consider the efficient estimation of total causal effects in the presence of unmeasured confounding using conditional instrumental sets. Specifically, we consider the two-stage least squares estimator in the setting of a linear structural equation
Externí odkaz:
http://arxiv.org/abs/2208.03697
Autor:
Su, Zehao, Henckel, Leonard
Publikováno v:
Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, PMLR (2022), 180:1886-1895
Suppose we want to estimate a total effect with covariate adjustment in a linear structural equation model. We have a causal graph to decide what covariates to adjust for, but are uncertain about the graph. Here, we propose a testing procedure, that
Externí odkaz:
http://arxiv.org/abs/2206.07533
Instrumental variable models allow us to identify a causal function between covariates $X$ and a response $Y$, even in the presence of unobserved confounding. Most of the existing estimators assume that the error term in the response $Y$ and the hidd
Externí odkaz:
http://arxiv.org/abs/2202.01864
Publikováno v:
Journal of Orthopaedic Surgery and Research, Vol 18, Iss 1, Pp 1-10 (2023)
Abstract Background Three-dimensional computed-tomography (3D-CT) planning for primary Total Hip Arthroplasty (THA) typically uses the external femoral surface; as a result, it is difficult to predict the prosthetic femoral version (PFV) for uncement
Externí odkaz:
https://doaj.org/article/b43a6c9df09b41c4923d39d1e8f5a50e
Publikováno v:
EFORT Open Reviews, Vol 8, Iss 11, Pp 809-817 (2023)
CT is the principal imaging modality used for the pre-operative 3D planning and assessment of total hip arthroplasty (THA). The image quality offered by CT has a radiation penalty to the patient. Higher than necessary radiation exposure is of particu
Externí odkaz:
https://doaj.org/article/95daaac6213a4007bb70431cb6d8ef5b