Zobrazeno 1 - 10
of 779
pro vyhledávání: '"Pasché P"'
Publikováno v:
World Journal of Surgical Oncology, Vol 7, Iss 1, p 101 (2009)
Abstract Background To assess functional results, complications, and success of larynx preservation in patients with recurrent squamous cell carcinoma after radiotherapy. Methods From a database of 40 patients who underwent supracricoid partial laryn
Externí odkaz:
https://doaj.org/article/5d5b093aa360452b8d3a82ef29144a0d
Autor:
Bodik, Juraj, Pasche, Olivier C.
We introduce a rigorous mathematical framework for Granger causality in extremes, designed to identify causal links from extreme events in time series. Granger causality plays a pivotal role in uncovering directional relationships among time-varying
Externí odkaz:
http://arxiv.org/abs/2407.09632
Autor:
Pasche, Olivier C., Wider, Jonathan, Zhang, Zhongwei, Zscheischler, Jakob, Engelke, Sebastian
The forecast accuracy of deep-learning-based weather prediction models is improving rapidly, leading many to speak of a "second revolution in weather forecasting". With numerous methods being developed, and limited physical guarantees offered by deep
Externí odkaz:
http://arxiv.org/abs/2404.17652
Publikováno v:
Extremes (2024)
This article summarizes the contribution of team genEVA to the EVA (2023) Conference Data Challenge. The challenge comprises four individual tasks, with two focused on univariate extremes and two related to multivariate extremes. In the first univari
Externí odkaz:
http://arxiv.org/abs/2401.14910
Autor:
Pasche, Olivier C., Engelke, Sebastian
Publikováno v:
Annals of Applied Statistics 18(4), 2818-2839 (2024)
Risk assessment for extreme events requires accurate estimation of high quantiles that go beyond the range of historical observations. When the risk depends on the values of observed predictors, regression techniques are used to interpolate in the pr
Externí odkaz:
http://arxiv.org/abs/2208.07590
Publikováno v:
Extremes 26(3), 573-594 (2023)
Confounding variables are a recurrent challenge for causal discovery and inference. In many situations, complex causal mechanisms only manifest themselves in extreme events, or take simpler forms in the extremes. Stimulated by data on extreme river f
Externí odkaz:
http://arxiv.org/abs/2110.06686
Autor:
Lyu, Qing, Namjoshi, Sanjeev V., McTyre, Emory, Topaloglu, Umit, Barcus, Richard, Chan, Michael D., Cramer, Christina K., Debinski, Waldemar, Gurcan, Metin N., Lesser, Glenn J., Lin, Hui-Kuan, Munden, Reginald F., Pasche, Boris C., Sai, Kiran Kumar Solingapuram, Strowd, Roy E., Tatter, Stephen B., Watabe, Kounosuke, Zhang, Wei, Wang, Ge, Whitlow, Christopher T.
Treatment decisions for brain metastatic disease rely on knowledge of the primary organ site, and currently made with biopsy and histology. Here we develop a novel deep learning approach for accurate non-invasive digital histology with whole-brain MR
Externí odkaz:
http://arxiv.org/abs/2110.03588
Autor:
Khorasani, Seyed Morteza Habibi, Lācis, Uǧis, Pasche, Simon, Rosti, Marco Edoardo, Bagheri, Shervin
Publikováno v:
Journal of Fluid Mechanics , Volume 942 , 10 July 2022 , A45
A set of boundary conditions called the Transpiration-Resistance Model (TRM) are investigated in altering near-wall turbulence. The TRM has been previously proposed by \citet{Lacis2020} as a means of representing the net effect of surface micro-textu
Externí odkaz:
http://arxiv.org/abs/2105.09391
Autor:
Chao, Hanqing, Fang, Xi, Zhang, Jiajin, Homayounieh, Fatemeh, Arru, Chiara D., Digumarthy, Subba R., Babaei, Rosa, Mobin, Hadi K., Mohseni, Iman, Saba, Luca, Carriero, Alessandro, Falaschi, Zeno, Pasche, Alessio, Wang, Ge, Kalra, Mannudeep K., Yan, Pingkun
While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been intensively studied, little work has been performed for image-based patient outcome prediction. Management of high-risk patients with early intervention is a key t
Externí odkaz:
http://arxiv.org/abs/2007.10416
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