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Published in 2022 at "Molecular Oncology"
DOI: 10.1002/1878-0261.13354
Abstract: The analysis of whole genomes of pan‐cancer data sets provides a challenge for researchers, and we contribute to the literature concerning the identification of robust subgroups with clear biological interpretation. Specifically, we tackle this unsupervised…
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Keywords:
pan cancer;
analysis;
based bayesian;
rank based ... See more keywords
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Published in 2022 at "International Journal for Numerical Methods in Biomedical Engineering"
DOI: 10.1002/cnm.3575
Abstract: This work introduces a computational methodology to calibrate material models in biomechanical applications under uncertainty. We adopt a Bayesian approach, which estimates the probability distributions of hyperelastic material parameters, based on force‐strain measurements. We approximate…
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Keywords:
bayesian calibration;
surrogate based;
methodology;
based bayesian ... See more keywords
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Published in 2022 at "Statistics in Medicine"
DOI: 10.1002/sim.9508
Abstract: To improve covariate balance over a complete randomization, a number of methods have been proposed recently to utilize modern computational capabilities to find allocations with balance in observed covariates. Asymptotic inference on treatment effects based…
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Keywords:
balance;
bayesian inference;
based bayesian;
inference ... See more keywords
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Published in 2024 at "Social Indicators Research"
DOI: 10.1007/s11205-023-03285-5
Abstract: This paper proposes spatial comprehensive composite indicators to evaluate the well-being levels and ranking of Italian provinces with data from the Equitable and Sustainable Well-Being dashboard. We use a method based on Bayesian latent factor…
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Keywords:
latent factor;
italian provinces;
spatial comprehensive;
composite indicators ... See more keywords
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Published in 2024 at "Statistics and Computing"
DOI: 10.1007/s11222-025-10715-6
Abstract: Bayesian Optimization (BO) is a powerful method for optimizing black-box functions by combining prior knowledge with ongoing function evaluations. BO constructs a probabilistic surrogate model of the objective function given the covariates, which is in…
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Keywords:
bayesian optimization;
model;
simulation based;
optimization ... See more keywords
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Published in 2017 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-015-0474-y
Abstract: Label noise is a common problem that affects supervised learning and can produce misleading results. It is shown that only $$5\,\%$$5% of switched labels lead to a decrease of performances. Therefore, the true class of…
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Keywords:
label;
bayesian aggregation;
based bayesian;
label denoising ... See more keywords
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Published in 2021 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2021.102054
Abstract: We develop a predictive prognosis model to support medical experts in their clinical decision-making process in Intensive Care Units (ICUs) (a) to enhance early mortality prediction, (b) to make more efficient medical decisions about patients…
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Keywords:
bayesian classifiers;
based bayesian;
intensive care;
model ... See more keywords
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Published in 2021 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2021.126559
Abstract: Abstract Simulating this ecological risk transmission process helps to judge the key path and propose the accurate urban risk control measures. This paper develops an urban ecological risk transmission conceptual framework based on Bayesian Network…
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Keywords:
risk transmission;
based bayesian;
urban ecological;
risk ... See more keywords
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Published in 2021 at "Journal of environmental sciences"
DOI: 10.1016/j.jes.2021.03.035
Abstract: Environmental impact of pollutants can be analyzed effectively by acquiring fish behavioral signals in water with biological behavior sensors. However, a variety of factors, such as the complexity of biological organisms themselves, the device error…
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Keywords:
bayesian sequential;
water;
fish behavioral;
method ... See more keywords
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Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-27486-z
Abstract: Individual-based models have become important tools in the global battle against infectious diseases, yet model complexity can make calibration to biological and epidemiological data challenging. We propose using a Bayesian optimization framework employing Gaussian process…
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Keywords:
individual based;
calibration;
based bayesian;
emulator based ... See more keywords
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Published in 2024 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2024.2425461
Abstract: Abstract Ideal point estimation methods in the social sciences lack a principled approach for identifying multidimensional ideal points. We present a novel method for estimating multidimensional ideal points based on l1 distance. In the Bayesian…
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Keywords:
ideal point;
ideal points;
politics;
multidimensional ideal ... See more keywords