Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Sally Cripps"'
Autor:
Mathew Varidel, Ian B. Hickie, Ante Prodan, Adam Skinner, Roman Marchant, Sally Cripps, Rafael Oliveria, Min K. Chong, Elizabeth Scott, Jan Scott, Frank Iorfino
Publikováno v:
npj Mental Health Research, Vol 3, Iss 1, Pp 1-9 (2024)
Abstract There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are ai
Externí odkaz:
https://doaj.org/article/4b545de43e014271be7d987639825d7c
Autor:
Wanchuang Zhu, Roman Marchant, Richard W. Morris, Louise A. Baur, Stephen J. Simpson, Sally Cripps
Publikováno v:
BMC Medicine, Vol 21, Iss 1, Pp 1-13 (2023)
Abstract Background When tackling complex public health challenges such as childhood obesity, interventions focused on immediate causes, such as poor diet and physical inactivity, have had limited success, largely because upstream root causes remain
Externí odkaz:
https://doaj.org/article/b8e8c5423b3f43deb4ed1585e0c700f6
Autor:
Frank Iorfino, Mathew Varidel, Roman Marchant, Sally Cripps, Jacob Crouse, Ante Prodan, Rafael Oliveria, Joanne S. Carpenter, Daniel F. Hermens, Adam Guastella, Elizabeth Scott, Jai Shah, Kathleen Merikangas, Jan Scott, Ian B. Hickie
Publikováno v:
Epidemiology and Psychiatric Sciences, Vol 32 (2023)
Abstract Aims The needs of young people attending mental healthcare can be complex and often span multiple domains (e.g., social, emotional and physical health factors). These factors often complicate treatment approaches and contribute to poorer out
Externí odkaz:
https://doaj.org/article/9985ad31b1e94666afa6587921bac87d
Autor:
Rafael Oliveira, Richard Scalzo, Robert Kohn, Sally Cripps, Kyle Hardman, John Close, Nasrin Taghavi, Charles Lemckert
Publikováno v:
Data-Centric Engineering, Vol 3 (2022)
Bayesian optimization (BO) has been a successful approach to optimize expensive functions whose prior knowledge can be specified by means of a probabilistic model. Due to their expressiveness and tractable closed-form predictive distributions, Gaussi
Externí odkaz:
https://doaj.org/article/08066c1c81cd45cdb9b4f040bea50a62
Autor:
Nathan Kettlewell, Richard W. Morris, Nick Ho, Deborah A. Cobb-Clark, Sally Cripps, Nick Glozier
Publikováno v:
SSM: Population Health, Vol 10, Iss , Pp - (2020)
Major life events affect our wellbeing. However the comparative impact of different events, which often co-occur, has not been systematically evaluated, or studies assumed that the impacts are equivalent in both amplitude and duration, that different
Externí odkaz:
https://doaj.org/article/aef1ba08487c44f2937d695cb8cf91ec
Autor:
Wanchuang Zhu, Roman Marchant, Richard W Morris, Louise A Baur, Stephen J Simpson, Sally Cripps
Background When tackling complex public health challenges such as childhood obesity, interventions focused on immediate causes, such as poor diet and physical inactivity, have had limited success, largely because upstream root causes remain unresolve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26aaea8a7183a8f7e3b5ba78d43fac98
https://doi.org/10.1101/2022.11.23.22282647
https://doi.org/10.1101/2022.11.23.22282647
Autor:
Guillaume Pirot, Richard Scalzo, Mark Jessell, M. Lindsay, Jeremie Giraud, Sally Cripps, Edward Cripps
Parametric geological models such as implicit or kinematic models provide low-dimensional, interpretable representations of 3-D geological structures. Combining these models with geophysical data in a probabilistic joint inversion framework provides
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10acd9253067b1fed3cf923c0ba5cd74
https://hdl.handle.net/10453/169653
https://hdl.handle.net/10453/169653
Publikováno v:
J Comput Graph Stat
We present the AdaptSPEC-X method for the joint analysis of a panel of possibly nonstationary time series. The approach is Bayesian and uses a covariate-dependent infinite mixture model to incorporate multiple time series, with mixture components par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d036da26268dc3afde8fc2160b9e610
Publikováno v:
Communications in Statistics - Simulation and Computation. 51:5288-5307
This article introduces a Bayesian multiple change point model for a collection of degradation signals in order to predict remaining useful life of rotational bearings. The model is designed for lo...
Publikováno v:
Neurocomputing. 359:315-326
Bayesian inference provides a rigorous approach for neural learning with knowledge representation via the posterior distribution that accounts for uncertainty quantification. Markov Chain Monte Carlo (MCMC) methods typically implement Bayesian infere