Zobrazeno 1 - 10
of 13 536
pro vyhledávání: '"Sisson A"'
Autor:
de Amorim, William E. R., Sisson, Scott A., Rodrigues, T., Nott, David J., Rodrigues, Guilherme S.
Positional Encoder Graph Neural Networks (PE-GNNs) are a leading approach for modeling continuous spatial data. However, they often fail to produce calibrated predictive distributions, limiting their effectiveness for uncertainty quantification. We i
Externí odkaz:
http://arxiv.org/abs/2409.18865
Calibration ensures that predicted uncertainties align with observed uncertainties. While there is an extensive literature on recalibration methods for univariate probabilistic forecasts, work on calibration for multivariate forecasts is much more li
Externí odkaz:
http://arxiv.org/abs/2409.10855
Symbolic data analysis (SDA) aggregates large individual-level datasets into a small number of distributional summaries, such as random rectangles or random histograms. Inference is carried out using these summaries in place of the original dataset,
Externí odkaz:
http://arxiv.org/abs/2408.04419
Max-stable processes serve as the fundamental distributional family in extreme value theory. However, likelihood-based inference methods for max-stable processes still heavily rely on composite likelihoods, rendering them intractable in high dimensio
Externí odkaz:
http://arxiv.org/abs/2407.13958
Artificial neural networks (ANNs) are highly flexible predictive models. However, reliably quantifying uncertainty for their predictions is a continuing challenge. There has been much recent work on "recalibration" of predictive distributions for ANN
Externí odkaz:
http://arxiv.org/abs/2403.05756
This paper presents asymptotic results for the maximum likelihood and restricted maximum likelihood (REML) estimators within a two-way crossed mixed effect model as the sizes of the rows, columns, and cells tend to infinity. Under very mild condition
Externí odkaz:
http://arxiv.org/abs/2401.06446
The application of deep learning techniques on aroma-chemicals has resulted in models more accurate than human experts at predicting olfactory qualities. However, public research in this domain has been limited to predicting the qualities of single m
Externí odkaz:
http://arxiv.org/abs/2312.16124
Gaussian process state-space models (GPSSMs) provide a principled and flexible approach to modeling the dynamics of a latent state, which is observed at discrete-time points via a likelihood model. However, inference in GPSSMs is computationally and
Externí odkaz:
http://arxiv.org/abs/2302.09921
Autor:
Lucy X. Li, Jessica S. Lin, Sean Tackett, Amanda Bertram, Stephen D. Sisson, Darius Rastegar, Megan E. Buresh
Publikováno v:
American Journal of Medicine Open, Vol 12, Iss , Pp 100077- (2024)
Background: The introduction of direct-acting antivirals (DAA) has revolutionized hepatitis C virus (HCV) treatment but has not translated into an appreciable decline in HCV prevalence, which is estimated to be 2.4 million in the United States. Effor
Externí odkaz:
https://doaj.org/article/4e03ce20aac24e4794f414fb49fd0543
Autor:
Simeon D. Kimmel, Jeffrey H. Samet, Debbie M. Cheng, Marina Vetrova, Bulat Idrisov, Sarah L. Rossi, Lindsey Rateau, Kristina Astone, Amy Michals, Emily Sisson, Elena Blokhina, Natasha Milet-Carty, Benjamin J. Bovell-Ammon, Natalia Gnatienko, Ve Truong, Evgeny Krupitsky, Karsten Lunze
Publikováno v:
Global Public Health, Vol 19, Iss 1 (2024)
Stigma that people with HIV who inject drugs experience negatively impacts HIV and substance use care, but stigma’s association with sharing injection equipment is not known. This is a cross-sectional analysis of data from two studies of people wit
Externí odkaz:
https://doaj.org/article/a1ba5ceb66914225a124d2e02c3f9fea