Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Beaulac, Cédric"'
Over the years, many approaches have been proposed to build ancestral recombination graphs (ARGs), graphs used to represent the genetic relationship between individuals. Among these methods, many rely on the assumption that the most likely graph is a
Externí odkaz:
http://arxiv.org/abs/2406.12022
Publikováno v:
Stat Comput 33:118 (2023)
The regression of a functional response on a set of scalar predictors can be a challenging task, especially if there is a large number of predictors, or the relationship between those predictors and the response is nonlinear. In this work, we propose
Externí odkaz:
http://arxiv.org/abs/2208.05776
Autor:
Beaulac, Cédric, Wu, Sidi, Gibson, Erin, Miranda, Michelle F., Cao, Jiguo, Rocha, Leno, Beg, Mirza Faisal, Nathoo, Farouk S.
Publikováno v:
BMC Bioinformatics 24, 271 (2023)
A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease
Externí odkaz:
http://arxiv.org/abs/2207.10794
Autor:
Mirabnahrazam, Ghazal, Ma, Da, Beaulac, Cédric, Lee, Sieun, Popuri, Karteek, Lee, Hyunwoo, Cao, Jiguo, Galvin, James E, Wang, Lei, Beg, Mirza Faisal, Initiative, the Alzheimer's Disease Neuroimaging
Publikováno v:
Neurobiology of Aging, 121, (2023), 139-156
Dementia of Alzheimer's Type (DAT) is a complex disorder influenced by numerous factors, but it is unclear how each factor contributes to disease progression. An in-depth examination of these factors may yield an accurate estimate of time-to-conversi
Externí odkaz:
http://arxiv.org/abs/2205.01188
Autor:
Beaulac, Cédric
Publikováno v:
Machine Learning (2023)
It can be difficult to assess the quality of a fitted model when facing unsupervised learning problems. Latent variable models, such as variation autoencoders and Gaussian mixture models, are often trained with likelihood-based approaches. In scope o
Externí odkaz:
http://arxiv.org/abs/2111.00875
Autor:
Beaulac, Cédric, Rosenthal, Jeffrey S.
Publikováno v:
SN COMPUT. SCI. 4, 66 (2023)
The contributions in this article are two-fold. First, we introduce a new hand-written digit data set that we collected. It contains high-resolution images of hand-written The contributions in this article are two-fold. First, we introduce a new hand
Externí odkaz:
http://arxiv.org/abs/2011.07946
Autor:
Beaulac, Cédric, Rosenthal, Jeffrey S., Pei, Qinglin, Friedman, Debra, Wolden, Suzanne, Hodgson, David
Publikováno v:
Applied Artificial Intelligence 2020
In this manuscript we analyze a data set containing information on children with Hodgkin Lymphoma (HL) enrolled on a clinical trial. Treatments received and survival status were collected together with other covariates such as demographics and clinic
Externí odkaz:
http://arxiv.org/abs/2001.05534
Autor:
Mirabnahrazam, Ghazal, Ma, Da, Beaulac, Cédric, Lee, Sieun, Popuri, Karteek, Lee, Hyunwoo, Cao, Jiguo, Galvin, James E, Wang, Lei, Beg, Mirza Faisal
Publikováno v:
In Neurobiology of Aging January 2023 121:139-156
In the following short article we adapt a new and popular machine learning model for inference on medical data sets. Our method is based on the Variational AutoEncoder (VAE) framework that we adapt to survival analysis on small data sets with missing
Externí odkaz:
http://arxiv.org/abs/1811.12323
Autor:
Beaulac, Cédric, Rosenthal, Jeffrey S.
Publikováno v:
Computational Statistics 2020
The main contribution of this paper is the development of a new decision tree algorithm. The proposed approach allows users to guide the algorithm through the data partitioning process. We believe this feature has many applications but in this paper
Externí odkaz:
http://arxiv.org/abs/1804.10168