LLM‐based prior elicitation for Bayesian graphical modeling
British Journal of Mathematical and Statistical Psychology, EarlyView.ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source
Multimodal brain-tumor segmentation based on Dirichlet process mixture model with anisotropic diffusion and Markov random field prior. [PDF]
Comput Math Methods Med, 2014 Lu Y, Jiang J, Yang W, Feng Q, Chen W.
europepmc +1 more source
On choosing the centering distribution in Dirichlet process mixture models
We present two results that pertain to the choosing of the centering distribution in a Bayesian setup with a Dirichlet process mixture prior based on Gaussian kernels.
Hanson, Timothy +2 more
core
Volume Quantization with Flexible Singularities for Hexahedral Meshing
Computer Graphics Forum, EarlyView.Abstract We present a novel algorithm for quantization and subsequent hexahedral mesh generation from seamless volumetric maps. Quantization is the process of choosing integers that represent the numbers of hexahedral elements to be placed in each region of the volume, and transforming the seamless map into an integer‐grid map matching that choice ...
H. Brückler, M. Campen
wiley +1 more source
Skeletal‐Driven Animation of Anatomical Humans via Neural Deformation Gradients
Computer Graphics Forum, EarlyView.Abstract Most real‐time animation techniques for digital humans are limited to deforming the outer skin surface. Geometric skinning methods are highly efficient but struggle with artifacts such as collapsing joints or self‐intersections when animating inner anatomy along with the outer skin.
G. Nolte +3 more
wiley +1 more source
scDAC: deep adaptive clustering of single-cell transcriptomic data with coupled autoencoder and Dirichlet process mixture model. [PDF]
BioinformaticsAn S +10 more
europepmc +1 more source
A spatial dirichlet process mixture model for clustering population genetics data. [PDF]
Biometrics, 2011 Reich BJ, Bondell HD.
europepmc +1 more source
Non‐Rigid 3D Shape Correspondences: From Foundations to Open Challenges and Opportunities
Computer Graphics Forum, EarlyView.Abstract Estimating correspondences between deformed shape instances is a long‐standing problem in computer graphics; numerous applications, from texture transfer to statistical modelling, rely on recovering an accurate correspondence map. Many methods have thus been proposed to tackle this challenging problem from varying perspectives, depending on ...
A. Zhuravlev +14 more
wiley +1 more source
Establishing Shape Correspondences: A Survey
Computer Graphics Forum, EarlyView.Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
wiley +1 more source